bluuebunny/crossref_metadata_2025 huggingface dataset:
A new diagnostic for tropospheric ozone production
Authors: Edwards Peter M. , Evans Mathew J.
Published: November 2017

Abstract. Tropospheric ozone is important for the Earth's climate and air quality. It is produced during the oxidation of organics in the presence of nitrogen oxides. Due to the range of organic species emitted and the chain-like nature of their oxidation, this chemistry is complex and understanding the role of different processes (emission, deposition, chemistry) is difficult. We demonstrate a new methodology for diagnosing ozone production based on the processing of bonds contained within emitted molecules, the fate of which is determined by the conservation of spin of the bonding electrons. Using this methodology to diagnose ozone production in the GEOS-Chem chemical transport model, we demonstrate its advantages over the standard diagnostic. We show that the number of bonds emitted, their chemistry and lifetime, and feedbacks on OH are all important in determining the ozone production within the model and its sensitivity to changes. This insight may allow future model–model comparisons to better identify the root causes of model differences.
Aerosol emissions factors from traditional biomass cookstoves in India: insights from field measurements
Authors: Pandey Apoorva , Patel Sameer , Pervez Shamsh , Tiwari Suresh , Yadama Gautam , Chow Judith C. , Watson John G. , Biswas Pratim , Chakrabarty Rajan K.
Published: November 2017

Abstract. Residential solid biomass cookstoves are important sources of aerosol emissions in India. Cookstove emissions rates are largely based on laboratory experiments conducted using the standard water-boiling test, but real-world emissions are often higher owing to different stove designs, fuels, and cooking methods. Constraining mass emissions factors (EFs) for prevalent cookstoves is important because they serve as inputs to bottom-up emissions inventories used to evaluate health and climate impacts. Real-world EFs were measured during winter 2015 for a traditional cookstove (chulha) burning fuel wood, agricultural residue, and dung from different regions of India. Average (±95 % confidence interval) EFs for fuel wood, agricultural residue, and dung were (1) PM2.5 mass: 10.5 (7.7–13.4) g kg−1, 11.1 (7.7–15.5) g kg−1, and 22.6 (14.9–32.9) g kg−1, respectively; (2) elemental carbon (EC): 0.9 (0.6–1.4) g kg−1, 1.6 (0.6–3.0) g kg−1, and 1.0 (0.4–2.0) g kg−1, respectively; and (3) organic carbon (OC): 4.9 (3.2–7.1) g kg−1, 7.0 (3.5–12.5) g kg−1, and 12.9 (4.2–15.01) g kg−1, respectively. The mean (±95 % confidence interval) OC ∕ EC mass ratios were 6.5 (4.5–9.1), 7.6 (4.4–12.2), and 12.7 (6.5–23.3), respectively, with OC and EC quantified by the IMPROVE_A thermal-optical reflectance protocol. These real-world EFs are higher than those from previous laboratory-based measurements. Combustion conditions have larger effects on EFs than the fuel types. We also report the carbon mass fractions of our aerosol samples determined using the thermal-optical reflectance method. The mass fraction profiles are consistent between the three fuel categories but markedly different from those reported in past literature – including the source profiles for wood stove PM2.5 emissions developed as inputs to receptor modeling studies conducted by the Central Pollution Control Board of India. Thermally stable OC (OC3 in the IMPROVE_A protocol) contributed nearly 50 % of the total carbon mass for emissions from all fuels.
Direct radiative effects of dust aerosols emitted from the Tibetan Plateau on the East Asian summer monsoon – a regional climate model simulation
Authors: Sun Hui , Liu Xiaodong , Pan Zaitao
Published: November 2017

Abstract. While dust aerosols emitted from major Asian sources such as Taklimakan and Gobi deserts have been shown to have strong effect on Asian monsoon and climate, the role of dust emitted from Tibetan Plateau (TP) itself, where aerosols can directly interact with the TP heat pump because of their physical proximity both in location and elevation, has not been examined. This study uses the dust-coupled RegCM4.1 regional climate model (RCM) to simulate the spatiotemporal distribution of dust aerosols originating within the TP and their radiative effects on the East Asian summer monsoon (EASM) during both heavy and light dust years. Two 20-year simulations with and without the dust emission from TP showed that direct radiative cooling in the mid-troposphere induced by the TP locally produced dust aerosols resulted in an overall anticyclonic circulation anomaly in the low troposphere centered over the TP region. The northeasterly anomaly in the EASM region reduces its strength considerably. The simulations found a significant negative correlation between the TP column dust load produced by local emissions and the corresponding anomaly in the EASM index (r = −0.46). The locally generated TP dust can cause surface cooling far downstream in Bohai Gulf and the China–North Korea border area through stationary Rossby wave propagation. Although dust from within TP (mainly Qaidam Basin) is a relatively small portion of total Asian aerosols, its impacts on Asian monsoon and climate seems disproportionately large, likely owning to its higher elevation within TP itself.
On the effect of upwind emission controls on ozone in Sequoia National Park
Authors: Buysse Claire E. , Munyan Jessica A. , Bailey Clara A. , Kotsakis Alexander , Sagona Jessica A. , Esperanza Annie , Pusede Sally E.
Published: November 2017

Abstract. Sequoia National Park (SNP) experiences the worst ozone (O3) pollution of any national park in the U.S. SNP is located on the western slope of the Sierra Nevada Mountains, downwind of the San Joaquin Valley (SJV), which is home to numerous cities ranked among the most O3-polluted in the U.S. Here, we investigate the influence of emission controls in the directly upwind SJV city of Visalia on O3 concentrations in SNP over a 12-yr time period (2001–2012). We show that export of nitrogen oxides (NOx) from the SJV plays a larger role in driving high O3 in SNP than does transport of O3. As a result, O3 in SNP has been more responsive to NOx emission reductions as a function of increasing downwind distance from the SJV. We report O3 trends by various concentration metrics, but do so separately for when environmental conditions are conducive to plant O3 uptake and for when high O3 is most common, which are time periods that occur at different times of day and year. We find that precursor emission controls have been less effective at reducing O3 concentrations in SNP in springtime, which is when plant O3 uptake in Sierra Nevada forests has been previously measured to be greatest. We discuss the implications of regulatory focus on high O3 days in SJV cities on O3 concentration trends and impacts in SNP.
Continuous Non-Marine Inputs of Per- and Polyfluoroalkyl Substances to the High Arctic: A Multi-Decadal Temporal Record
Authors: Pickard Heidi M. , Criscitiello Alison S. , Spencer Christine , Sharp Martin J. , Muir Derek C. G. , De Silva Amila O. , Young Cora J.
Published: November 2017

Abstract. Perfluoroalkyl acids (PFAAs) are persistent, bioaccumulative compounds found ubiquitously within the environment. They can be formed from the atmospheric oxidation of volatile precursor compounds and undergo long-range transport through the atmosphere and ocean to remote locations. Ice caps preserve a temporal record of PFAA deposition making them useful in studying the atmospheric trends in LRT of PFAAs as well as understanding major pollutant sources and production changes over time. A 15 m ice core representing 38 years of deposition (1977–2015) was collected from the Devon Ice Cap in Nunavut, providing us with the first multi-decadal temporal ice record in PFAA deposition to the Arctic. Ice core samples were concentrated using solid phase extraction and analyzed by liquid and ion chromatography methods. Both perfluoroalkyl carboxylic acids (PFCAs) and perfluoroalkyl sulfonic acids (PFSAs) were detected in the samples, with fluxes ranging from
Cloud Condensation Nuclei Activity of CaCO3 Particles with Oleic Acid and Malonic Acid Coatings
Authors: Wang Mingjin , Zhu Tong , Zhao Defeng , Rubach Florian , Wahner Andreas , Kiendler-Scharr Astrid , Mentel Thomas F.
Published: November 2017

Abstract. Condensation of carboxylic acids on mineral particles will lead to coatings, and impact on the particles' potential to act as cloud condensation nuclei (CCN). To determine how the CCN activity of mineral particles is impacted by carboxylic acid coatings, the CCN activity of CaCO3 particles and CaCO3 particles with oleic acid and malonic acid coatings were compared in this study. The results revealed that small amounts of oleic acid coating (volume fraction (vf) ≤ 4.1 %) decreased the CCN activity of CaCO3 particles, while more oleic acid coating (vf ≥ 14.8 %) increased the CCN activity of CaCO3 particles. This phenomenon has not been reported before. On the other hand, malonic acid coating (vf = 0.4–42 %) increased the CCN activity of CaCO3 particles regardless of the amount of the coating. The CCN activity of CaCO3 particles with malonic acid coating increased with the amount of malonic acid coating. Even smallest amounts of malonic acid coating (vf = 0.4 %) significantly enhanced the CCN activity of CaCO3 particles from κ = 0.0028 ± 0.0001 to κ = 0.0123 ± 0.0005. This supports that a small amount of water-soluble organic acid coating may significantly enhance the CCN activity of mineral particles. The presence of about 50 % relative humidity during the coating process with malonic acid additionally increased the CCN activity of the coated CaCO3 particles, probably because more CaCO3 reacts with malonic acid at higher relative humidity.
Improving Mobile Platform Gaussian-Derived Emission Estimates Using Hierarchical Sampling and Large Eddy Simulation
Authors: Caulton Dana R. , Li Qi , Bou-Zeid Elie , Lu Jessica , Lane Haley M. , Fitts Jeffrey P. , Buchholz Bernhard , Golston Levi M. , Guo Xuehui , McSpiritt James , Pan Da , Wendt Lars , Zondlo Mark A.
Published: November 2017

Abstract. Mobile laboratory measurements provide information on the distribution of CH4 emissions from point sources such as oil and gas wells, but uncertainties are poorly constrained or justified. Sources of uncertainty and bias in ground-based Gaussian derived emissions estimates from a mobile platform were analyzed in a combined field and modeling study. In a field campaign where 1009 natural gas sites in Pennsylvania were sampled, a hierarchical measurement strategy was implemented with increasing complexity. Of these sites, ~ 93 % were sampled with an average of 2 transects (standard sampling), ~ 5 % were sampled with an average of 10 transects (replicate sampling) and ~ 2 % were sampled with an average of 20 transects while simultaneously deploying a tower to measure high-frequency meteorological data (intensive sampling). Five of the intensive sampling sites were modeled using large eddy simulation (LES) to reproduce CH4 concentrations in a turbulent environment. The LES output and derived emission estimates were used to compare with the results of a standard Gaussian approach. The LES and Gaussian derived emission rates agreed within a factor of 2, in most cases with average differences of 25 %. A controlled release was also used to investigate sources of bias in either technique. The Gaussian agreed with the release rate more closely than the LES underlying the importance of inputs as sources of uncertainty for the LES. The LES was also used as a virtual experiment to investigate optimum number of repeat transects and spacing needed to produce representative statistics. Approximately 10 repeat transects spaced at least 1 min apart are required to produce statistics similar to the observed variability over the entire LES simulation period of 30 min. In addition, other sources of uncertainty including source location, wind speed and stability were analyzed. In total, atmospheric variability, observed by repeat measurements at individual sites under relatively constant conditions, was found to be the most significant contributor to total uncertainty. Accurate measurements of this condition provide a reasonable estimate of the lower bound for emission uncertainty. It is recommended that future mobile monitoring schemes quantify this metric under representative conditions to accurately estimate emission uncertainty.
Quantification of the effect of modeled lightning NO2 on UV–visible air mass factors
Authors: Laughner Joshua L. , Cohen Ronald C.
Published: November 2017

Abstract. Space-borne measurements of tropospheric nitrogen dioxide (NO2) columns are up to 10x more sensitive to upper tropospheric (UT) NO2 than near-surface NO2 over low-reflectivity surfaces. Here, we quantify the effect of adding simulated lightning NO2 to the a priori profiles for NO2 observations from the Ozone Monitoring Instrument (OMI) using modeled NO2 profiles from the Weather Research and Forecasting–Chemistry (WRF-Chem) model. With observed NO2 profiles from the Deep Convective Clouds and Chemistry (DC3) aircraft campaign as observational truth, we quantify the bias in the NO2 column that occurs when lightning NO2 is not accounted for in the a priori profiles. Focusing on late spring and early summer in the central and eastern United States, we find that a simulation without lightning NO2 underestimates the air mass factor (AMF) by 25 % on average for common summer OMI viewing geometry and 35 % for viewing geometries that will be encountered by geostationary satellites. Using a simulation with 500 to 665 mol NO flash−1 produces good agreement with observed NO2 profiles and reduces the bias in the AMF to  <  ±4 % for OMI viewing geometries. The bias is regionally dependent, with the strongest effects in the southeast United States (up to 80 %) and negligible effects in the central US. We also find that constraining WRF meteorology to a reanalysis dataset reduces lightning flash counts by a factor of 2 compared to an unconstrained run, most likely due to changes in the simulated water vapor profile.
Comparative assessment of GRASP algorithm for a dust event over Granada (Spain) during ChArMEx-ADRIMED 2013 campaign
Authors: Benavent-Oltra Jose A. , Román Roberto , Granados-Muñoz María J. , Pérez-Ramírez Daniel , Ortiz-Amezcua Pablo , Denjean Cyrielle , Lopatin Anton , Lyamani Hassan , Torres Benjamin , Guerrero-Rascado Juan L. , Fuertes David , Dubovik Oleg , Chaikovsky Anatoli , Olmo Francisco J. , Mallet Marc , Alados-Arboledas Lucas
Published: November 2017

Abstract. In this study, vertical profiles and column-integrated aerosol properties retrieved by the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm are evaluated with in situ airborne measurements made during the ChArMEx-ADRIMED field campaign in summer 2013. In the framework of this campaign, two different flights took place over Granada (Spain) during a desert dust episode on 16 and 17 June. The GRASP algorithm, which combines lidar and sun–sky photometer data measured at Granada, was used to retrieve aerosol properties. Two sun-photometer datasets are used: one co-located with the lidar system and the other in the Cerro Poyos station, approximately 1200 m higher than the lidar system but at a short horizontal distance. Column-integrated aerosol microphysical properties retrieved by GRASP are compared with AERONET products showing a good agreement. Differences between GRASP retrievals and airborne extinction profiles are in the range of 15 to 30 %, depending on the instrument on board the aircraft used as reference. On 16 June, a case where the dust layer was coupled to the aerosol layer close to surface, the total volume concentration differences between in situ data and GRASP retrieval are 15 and 36 % for Granada and Cerro Poyos retrievals, respectively. In contrast, on 17 June the dust layer was decoupled from the aerosol layer close to the surface, and the differences are around 17 % for both retrievals. In general, all the discrepancies found are within the uncertainly limits, showing the robustness and reliability of the GRASP algorithm. However, the better agreement found for the Cerro Poyos retrieval with the aircraft data and the vertical homogeneity of certain properties retrieved with GRASP, such as the scattering Ångström exponent, for cases with aerosol layers characterized by different aerosol types, shows that uncertainties in the vertical distribution of the aerosol properties have to be considered. The comparison presented here between GRASP and other algorithms (i.e. AERONET and LIRIC) and with airborne in situ measurements shows the potential to retrieve the optical and microphysical profiles of the atmospheric aerosol properties. Also, the advantage of GRASP versus LIRIC is that GRASP does not assume the results of the AERONET inversion as a starting point.
Reconstructing Late Holocene North Atlantic atmospheric circulation changes using functional paleoclimate networks
Authors: Franke Jasper G. , Werner Johannes P. , Donner Reik V.
Published: November 2017

Abstract. Obtaining reliable reconstructions of long-term atmospheric circulation changes in the North Atlantic region presents a persistent challenge to contemporary paleoclimate research, which has been addressed by a multitude of recent studies. In order to contribute a novel methodological aspect to this active field, we apply here evolving functional network analysis, a recently developed tool for studying temporal changes of the spatial co-variability structure of the Earth's climate system, to a set of Late Holocene paleoclimate proxy records covering the last two millennia. The emerging patterns obtained by our analysis are related to long-term changes in the dominant mode of atmospheric circulation in the region, the North Atlantic Oscillation (NAO). By comparing the time-dependent inter-regional linkage structures of the obtained functional paleoclimate network representations to a recent multi-centennial NAO reconstruction, we identify co-variability between southern Greenland, Svalbard, and Fennoscandia as being indicative of a positive NAO phase, while connections from Greenland and Fennoscandia to central Europe are more pronounced during negative NAO phases. By drawing upon this correspondence, we use some key parameters of the evolving network structure to obtain a qualitative reconstruction of the NAO long-term variability over the entire Common Era (last 2000 years) using a linear regression model trained upon the existing shorter reconstruction.
Parcels v0.9: prototyping a Lagrangian ocean analysis framework for the petascale age
Authors: Lange Michael , van Sebille Erik
Published: November 2017

Abstract. As ocean general circulation models (OGCMs) move into the petascale age, where the output of single simulations exceeds petabytes of storage space, tools to analyse the output of these models will need to scale up too. Lagrangian ocean analysis, where virtual particles are tracked through hydrodynamic fields, is an increasingly popular way to analyse OGCM output, by mapping pathways and connectivity of biotic and abiotic particulates. However, the current software stack of Lagrangian ocean analysis codes is not dynamic enough to cope with the increasing complexity, scale and need for customization of use-cases. Furthermore, most community codes are developed for stand-alone use, making it a nontrivial task to integrate virtual particles at runtime of the OGCM. Here, we introduce the new Parcels code, which was designed from the ground up to be sufficiently scalable to cope with petascale computing. We highlight its API design that combines flexibility and customization with the ability to optimize for HPC workflows, following the paradigm of domain-specific languages. Parcels is primarily written in Python, utilizing the wide range of tools available in the scientific Python ecosystem, while generating low-level C code and using just-in-time compilation for performance-critical computation. We show a worked-out example of its API, and validate the accuracy of the code against seven idealized test cases. This version 0.9 of Parcels is focused on laying out the API, with future work concentrating on support for curvilinear grids, optimization, efficiency and at-runtime coupling with OGCMs.
Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling
Authors: Auvinen Mikko , Järvi Leena , Hellsten Antti , Rannik Üllar , Vesala Timo
Published: November 2017

Abstract. Conventional footprint models cannot account for the heterogeneity of the urban landscape imposing a pronounced uncertainty on the spatial interpretation of eddy-covariance (EC) flux measurements in urban studies. This work introduces a computational methodology that enables the generation of detailed footprints in arbitrarily complex urban flux measurements sites. The methodology is based on conducting high-resolution large-eddy simulation (LES) and Lagrangian stochastic (LS) particle analysis on a model that features a detailed topographic description of a real urban environment. The approach utilizes an arbitrarily sized target volume set around the sensor in the LES domain, to collect a dataset of LS particles which are seeded from the potential source area of the measurement and captured at the sensor site. The urban footprint is generated from this dataset through a piecewise postprocessing procedure, which divides the footprint evaluation into multiple independent processes that each yield an intermediate result. These results are ultimately selectively combined to produce the final footprint. The strategy reduces the computational cost of the LES–LS simulation and incorporates techniques to account for the complications that arise when the EC sensor is mounted on a building instead of a conventional flux tower. The presented computational framework also introduces a result assessment strategy which utilizes the obtained urban footprint together with a detailed land cover type dataset to estimate the potential error that may arise if analytically derived footprint models were employed instead. The methodology is demonstrated with a case study that concentrates on generating the footprint for a building-mounted EC measurement station in downtown Helsinki, Finland, under the neutrally stratified atmospheric boundary layer.
EDDA 2.0: integrated simulation of debris flow initiation and dynamics,
considering two initiation mechanisms
Authors: Shen Ping , Zhang Limin , Chen Hongxin , Fan Ruilin
Published: November 2017

Abstract. Climate change results in more frequent rainstorms and more rain-induced debris flows in mountainous areas. The prediction of likely hazard zones is important for debris flow risk assessment and management. Existing numerical methods for debris flow analysis often require the input of hydrographs at prescribed initiation locations, ignoring the initiation process and leading to large uncertainties in debris flow initiation locations, times and volumes when applied to regional debris flow analysis. The evolution of the flowing mixture in time and space is hardly addressed either. This paper presents a new integrated numerical model, EDDA 2.0, to simulate the whole process of debris-flow initiation, motion, entrainment, deposition and property changes. Two physical initiation mechanisms are modeled: transformation from slope failures and surface erosion. Three numerical tests and field application to a catastrophic debris flow event are conducted to verify the model components and evaluate the model performance. The results indicate that the integrated model is capable of simulating the initiation and subsequent flowing process of rain-induced debris flows, as well as the physical evolution of the flowing mixture. The integrated model provides a powerful tool for analyzing multi-hazard processes, hazard interactions and regional debris-flow risk assessment in the future.
Comparison of dealiasing schemes in large-eddy simulation of neutrally-stratified atmospheric boundary-layer type flows
Authors: Margairaz Fabien , Giometto Marco G. , Parlange Marc B. , Calaf Marc
Published: November 2017

Abstract. Three dealiasing schemes for large-eddy simulation of turbulent flows are inter-compared for the canonical case of pressure-drive atmospheric boundary-layer type flows. Aliasing errors arise in the multiplication of partial sums, such as those encountered when integrating the non-linear terms of the Navier–Stokes equations in spectral methods (Fourier or polynomial discrete series), and are detrimental to the accuracy of the numerical solution. This is of special relevance when using high-order schemes. In this work, a performance/cost analysis is developed for three well-accepted approaches: the exact 3/2 rule, the Fourier truncation method, and a high order Fourier smoothing method. Tests are performed within a newly developed mixed pseudo-spectral collocation - finite differences large-eddy simulation code, parallelized using a two-dimensional pencil decomposition. The static Smagorinsky eddy-viscosity model with wall damping of the model coefficient is used. A series of simulations are performed at varying resolution and key flow statistics are inter-compared among the considered dealiasing schemes. The numerical results validate the numerical performance predicted by theory when using the Fourier truncation and Fourier smoothing methods. In terms of turbulence statistics, the Fourier Truncation method proves to be over-dissipative when compared against the Fourier Smoothing method and the traditional 3/2-rule, leading to an enhanced horizontal integrated mass flux and to higher dispersive momentum fluxes. Its use in large-eddy simulation of atmospheric boundary-layer type flows is therefore not recommended. Conversely, the Fourier Smoothing method yields accurate flow statistics, comparable to those resulting from the application of the 3/2 rule, with a significant reduction in computational cost, which makes it a convenient alternative for use in the studies related to the atmospheric boundary layer.
New insights into the differences between the dual node approach and the common node approach for coupling surface–subsurface flow
Authors: de Rooij Rob
Published: November 2017

Abstract. The common node approach and the dual node approach are two widely applied approaches to coupling surface–subsurface flow. In this study both approaches are analyzed for cell-centered as well as vertex-centered finite difference schemes. It is shown that the dual node approach should be conceptualized and implemented as a one-sided first-order finite difference to approximate the vertical subsurface hydraulic gradient at the land surface. This results in a consistent dual node approach in which the coupling length is related to grid topology. In this coupling approach the coupling length is not to be interpreted as a nonphysical model parameter. Although this particular coupling approach is technically not new, the differences between this consistent dual node approach and the common node approach have not been studied in detail. In fact, this coupling scheme is often believed to be similar to the common node approach. In this study it is illustrated that in comparison to the common node approach, the head continuity at the surface–subsurface interface is formulated more correctly in the consistent dual node approach. Numerical experiments indicate that the consistent dual node approach is less sensitive to the vertical discretization when simulating excess infiltration. It is also found that the consistent dual node approach can be advantageous in terms of numerical efficiency.
Impact of snow deposition on major and trace element concentrations and elementary fluxes in surface waters of the Western Siberian Lowland across a 1700 km latitudinal gradient
Authors: Shevchenko Vladimir P. , Pokrovsky Oleg S. , Vorobyev Sergey N. , Krickov Ivan V. , Manasypov Rinat M. , Politova Nadezhda V. , Kopysov Sergey G. , Dara Olga M. , Auda Yves , Shirokova Liudmila S. , Kolesnichenko Larisa G. , Zemtsov Valery A. , Kirpotin Sergey N.
Published: November 2017

Abstract. In order to better understand the chemical composition of snow and its impact on surface water hydrochemistry in the poorly studied Western Siberia Lowland (WSL), the surface layer of snow was sampled in February 2014 across a 1700 km latitudinal gradient (ca. 56.5 to 68° N). We aimed at assessing the latitudinal effect on both dissolved and particulate forms of elements in snow and quantifying the impact of atmospheric input to element storage and export fluxes in inland waters of the WSL. The concentration of dissolved+colloidal (< 0.45 µm) Fe, Co, Cu, As and La increased by a factor of 2 to 5 north of 63° N compared to southern regions. The pH and dissolved Ca, Mg, Sr, Mo and U in snow water increased with the rise in concentrations of particulate fraction (PF). Principal component analyses of major and trace element concentrations in both dissolved and particulate fractions revealed two factors not linked to the latitude. A hierarchical cluster analysis yielded several groups of elements that originated from alumino-silicate mineral matrix, carbonate minerals and marine aerosols or belonging to volatile atmospheric heavy metals, labile elements from weatherable minerals and nutrients. The main sources of mineral components in PF are desert and semi-desert regions of central Asia. The snow water concentrations of DIC, Cl, SO4, Mg, Ca, Cr, Co, Ni, Cu, Mo, Cd, Sb, Cs, W, Pb and U exceeded or were comparable with springtime concentrations in thermokarst lakes of the permafrost-affected WSL zone. The springtime river fluxes of DIC, Cl, SO4, Na, Mg, Ca, Rb, Cs, metals (Cr, Co, Ni, Cu, Zn, Cd, Pb), metalloids (As, Sb), Mo and U in the discontinuous to continuous permafrost zone (64–68° N) can be explained solely by melting of accumulated snow. The impact of snow deposition on riverine fluxes of elements strongly increased northward, in discontinuous and continuous permafrost zones of frozen peat bogs. This was consistent with the decrease in the impact of rock lithology on river chemical composition in the permafrost zone of the WSL, relative to the permafrost-free regions. Therefore, the present study demonstrates significant and previously underestimated atmospheric input of many major and trace elements to their riverine fluxes during spring floods. A broader impact of this result is that current estimations of river water fluxes response to climate warming in high latitudes may be unwarranted without detailed analysis of winter precipitation.
LASER SCANNER TECHNOLOGY, GROUND-PENETRATING RADAR AND AUGMENTED REALITY FOR THE SURVEY AND RECOVERY OF ARTISTIC, ARCHAEOLOGICAL AND CULTURAL HERITAGE
Authors: Barrile V. , Bilotta G. , Meduri G. M. , De Carlo D. , Nunnari A.
Published: November 2017

Abstract. In this study, using technologies such as laser scanner and GPR it was desired to see their potential in the cultural heritage. Also with regard to the processing part we are compared the results obtained by the various commercial software and algorithms developed and implemented in Matlab. Moreover, Virtual Reality and Augmented Reality allow integrating the real world with historical-artistic information, laser scanners and georadar (GPR) data and virtual objects, virtually enriching it with multimedia elements, graphic and textual information accessible through smartphones and tablets.
IMPACT OF FLOODING ON LAND USE/ LAND COVER TRANSFORMATION IN WULAR LAKE AND ITS ENVIRONS, KASHMIR VALLEY, INDIA USING GEOINFORMATICS
Authors: Ahmad T. , Pandey A. C. , Kumar A.
Published: November 2017

Abstract. Wular lake, located at an elevation of 1520 m above sea level in Kashmir valley, India. In the present study, the immediate and long term impact of flood (2014) over the Wular lake environs was analyzed by using satellite images and employing supervised classification technique in GIS environment. The LULC classification was performed on the images of 25th August 2014 (pre flood) and 13th September 2015 (post flood) and was compared, which indicated marked decrease in terrestrial vegetation (23.7 %), agriculture (43.7 %) and water bodies (39.9 %). Overlaying analysis was performed with pre and post flood classified images with reference to the satellite image of 10th September 2014(during flood) which indicated total area inundated during flood was 88.77 km2. With the pre-flood situation, the aquatic vegetation of 34.06 km2, 13.89 km2 of agriculture land and terrestrial vegetation of 3.13 km2 was inundated. In the post flood situation, it was also came into focus that more than the half of the area under water bodies was converted into sand deposits (22.76 km2) due to anomalous increase in siltation. The overlay analysis on post flood classified image indicated that aquatic vegetation followed by agriculture and sand deposits lie within the flood inundated area. Further spatial analysis was performed within the flood inundated area (88.77 km2) with pre and post classified image to understand the situation before and after the flood and to calculate the changes. These land use-land cover transformations signifies the ill effect of flooding on the biodiversity of Wular Lake.
THE EFFICIENCY OF RANDOM FOREST METHOD FOR SHORELINE EXTRACTION FROM LANDSAT-8 AND GOKTURK-2 IMAGERIES
Authors: Bayram B. , Erdem F. , Akpinar B. , Ince A. K. , Bozkurt S. , Catal Reis H. , Seker D. Z.
Published: November 2017

Abstract. Coastal monitoring plays a vital role in environmental planning and hazard management related issues. Since shorelines are fundamental data for environment management, disaster management, coastal erosion studies, modelling of sediment transport and coastal morphodynamics, various techniques have been developed to extract shorelines. Random Forest is one of these techniques which is used in this study for shoreline extraction.. This algorithm is a machine learning method based on decision trees. Decision trees analyse classes of training data creates rules for classification. In this study, Terkos region has been chosen for the proposed method within the scope of "TUBITAK Project (Project No: 115Y718) titled "Integration of Unmanned Aerial Vehicles for Sustainable Coastal Zone Monitoring Model – Three-Dimensional Automatic Coastline Extraction and Analysis: Istanbul-Terkos Example". Random Forest algorithm has been implemented to extract the shoreline of the Black Sea where near the lake from LANDSAT-8 and GOKTURK-2 satellite imageries taken in 2015. The MATLAB environment was used for classification. To obtain land and water-body classes, the Random Forest method has been applied to NIR bands of LANDSAT-8 (5th band) and GOKTURK-2 (4th band) imageries. Each image has been digitized manually and shorelines obtained for accuracy assessment. According to accuracy assessment results, Random Forest method is efficient for both medium and high resolution images for shoreline extraction studies.
COMPARISON OF TWO SIMPLIFICATION METHODS FOR SHORELINE EXTRACTION FROM DIGITAL ORTHOPHOTO IMAGES
Authors: Bayram B. , Sen A. , Selbesoglu M. O. , Vārna I. , Petersons P. , Aykut N. O. , Seker D. Z.
Published: November 2017

Abstract. The coastal ecosystems are very sensitive to external influences. Coastal resources such as sand dunes, coral reefs and mangroves has vital importance to prevent coastal erosion. Human based effects also threats the coastal areas. Therefore, the change of coastal areas should be monitored. Up-to-date, accurate shoreline information is indispensable for coastal managers and decision makers. Remote sensing and image processing techniques give a big opportunity to obtain reliable shoreline information. In the presented study, NIR bands of seven 1:5000 scaled digital orthophoto images of Riga Bay-Latvia have been used. The Object-oriented Simple Linear Clustering method has been utilized to extract shoreline of Riga Bay. Bend and Douglas-Peucker methods have been used to simplify the extracted shoreline to test the effect of both methods. Photogrammetrically digitized shoreline has been taken as reference data to compare obtained results. The accuracy assessment has been realised by Digital Shoreline Analysis tool. As a result, the achieved shoreline by the Bend method has been found closer to the extracted shoreline with Simple Linear Clustering method.
SPATIAL PREDICTION OF AIR TEMPERATURE IN EAST CENTRAL ANATOLIA OF TURKEY
Authors: Bilgili B. C. , Erşahin S. , Özyavuz M.
Published: November 2017

Abstract. Air temperature is an essential component of the factors used in landscape planning. At similar topographic conditions, vegetation may show considerable differences depending on air temperature and precipitation. In large areas, measuring temperature is a cost and time-consuming work. Therefore, prediction of climate variables at unmeasured sites at an acceptable accuracy is very important in regional resource planning. In addition, use a more proper prediction method is crucial since many different prediction techniques yield different performance in different landscape and geographical conditions. We compared inverse distance weighted (IDW), ordinary kriging (OK), and ordinary cokriging (OCK) to predict air temperature at unmeasured sites in Malatya region (East Central Anatolia) of Turkey. Malatya region is the most important apricot production area of Turkey and air temperature is the most important factor determining the apricot growing zones in this region. We used mean monthly temperatures from 1975 to 2010 measured at 28 sites in the study area and predicted temperature with IDW, OC, and OCK techniques, mapped temperature in the region, and tested the reliability of these maps. The OCK with elevation as an auxiliary variable occurred the best procedure to predict temperature against the criteria of model efficiency and relative root mean squared error.
USING 3D BIM MODEL FOR THE VALUE-BASED LAND SHARE CALCULATIONS
Authors: Çelik Şimşek N. , Uzun B.
Published: November 2017

Abstract. According to the Turkish condominium ownership system, 3D physical buildings and its condominium units are registered to the condominium ownership books via 2D survey plans. Currently, 2D representations of the 3D physical objects, causes inaccurate and deficient implementations for the determination of the land shares. Condominium ownership and easement right are established with a clear indication of land shares (condominium ownership law, article no. 3). So, the land share of each condominium unit have to be determined including the value differences among the condominium units. However the main problem is that, land share has often been determined with area based over the project before construction of the building. The objective of this study is proposing a new approach in terms of value-based land share calculations of the condominium units that subject to condominium ownership. So, the current approaches and its failure that have taken into account in determining the land shares are examined. And factors that affect the values of the condominium units are determined according to the legal decisions. This study shows that 3D BIM models can provide important approaches for the valuation problems in the determination of the land shares.
CREATING DIGITAL ELEVATION MODEL USING A MOBILE DEVICE
Authors: Durmaz A. İ.
Published: November 2017

Abstract. DEM (Digital Elevation Models) is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices’ GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.
RETHINKING INDOOR LOCALIZATION SOLUTIONS TOWARDS THE FUTURE OF MOBILE LOCATION-BASED SERVICES
Authors: Guney C.
Published: November 2017

Abstract. Satellite navigation systems with GNSS-enabled devices, such as smartphones, car navigation systems, have changed the way users travel in outdoor environment. GNSS is generally not well suited for indoor location and navigation because of two reasons: First, GNSS does not provide a high level of accuracy although indoor applications need higher accuracies. Secondly, poor coverage of satellite signals for indoor environments decreases its accuracy. So rather than using GNSS satellites within closed environments, existing indoor navigation solutions rely heavily on installed sensor networks. There is a high demand for accurate positioning in wireless networks in GNSS-denied environments. However, current wireless indoor positioning systems cannot satisfy the challenging needs of indoor location-aware applications. Nevertheless, access to a user’s location indoors is increasingly important in the development of context-aware applications that increases business efficiency. In this study, how can the current wireless location sensing systems be tailored and integrated for specific applications, like smart cities/grids/buildings/cars and IoT applications, in GNSS-deprived areas.
MODELLING PARTICIPATORY GEOGRAPHIC INFORMATION SYSTEM FOR CUSTOMARY LAND CONFLICT RESOLUTION
Authors: Gyamera E. A. , Arko-Adjei A. , Duncan E. E. , Kuma J. S. Y.
Published: November 2017

Abstract. Since land contributes to about 73 % of most countries Gross Domestic Product (GDP), attention on land rights have tremendously increased globally. Conflicts over land have therefore become part of the major problems associated with land administration. However, the conventional mechanisms for land conflict resolution do not provide satisfactory result to disputants due to various factors. This study sought to develop a Framework of using Participatory Geographic Information System (PGIS) for customary land conflict resolution. The framework was modelled using Unified Modelling Language (UML). The PGIS framework, called butterfly model, consists of three units namely, Social Unit (SU), Technical Unit (TU) and Decision Making Unit (DMU). The name butterfly model for land conflict resolution was adopted for the framework based on its features and properties. The framework has therefore been recommended to be adopted for land conflict resolution in customary areas.
GIS-BASED MULTI-CRITERIA DECISION ANALYSIS FOR FOREST FIRE RISK MAPPING
Authors: Akay A. E. , Erdoğan A.
Published: November 2017

Abstract. The forested areas along the coastal zone of the Mediterranean region in Turkey are classified as first-degree fire sensitive areas. Forest fires are major environmental disaster that affects the sustainability of forest ecosystems. Besides, forest fires result in important economic losses and even threaten human lives. Thus, it is critical to determine the forested areas with fire risks and thereby minimize the damages on forest resources by taking necessary precaution measures in these areas. The risk of forest fire can be assessed based on various factors such as forest vegetation structures (tree species, crown closure, tree stage), topographic features (slope and aspect), and climatic parameters (temperature, wind). In this study, GIS-based Multi-Criteria Decision Analysis (MCDA) method was used to generate forest fire risk map. The study was implemented in the forested areas within Yayla Forest Enterprise Chiefs at Dursunbey Forest Enterprise Directorate which is classified as first degree fire sensitive area. In the solution process, "extAhp 2.0" plug-in running Analytic Hierarchy Process (AHP) method in ArcGIS 10.4.1 was used to categorize study area under five fire risk classes: extreme risk, high risk, moderate risk, and low risk. The results indicated that 23.81 % of the area was of extreme risk, while 25.81 % was of high risk. The result indicated that the most effective criterion was tree species, followed by tree stages. The aspect had the least effective criterion on forest fire risk. It was revealed that GIS techniques integrated with MCDA methods are effective tools to quickly estimate forest fire risk at low cost. The integration of these factors into GIS can be very useful to determine forested areas with high fire risk and also to plan forestry management after fire.
A COMPREHENSIVE REVIEW OF PANSHARPENING ALGORITHMS FOR GÖKTÜRK-2 SATELLITE IMAGES
Authors: Kahraman S. , Ertürk A.
Published: November 2017

Abstract. In this paper, a comprehensive review and performance evaluation of pansharpening algorithms for GÖKTÜRK-2 images is presented. GÖKTÜRK-2 is the first high resolution remote sensing satellite of Turkey which was designed and built in Turkey, by The Ministry of Defence, TUBITAK-UZAY and Turkish Aerospace Industry (TUSAŞ) collectively. GÖKTÜRK-2 was launched at 18th. December 2012 in Jinguan, China and provides 2.5 meter panchromatic (PAN) and 5 meter multispectral (MS) spatial resolution satellite images. In this study, a large number of pansharpening algorithms are implemented and evaluated for performance on multiple GÖKTÜRK-2 satellite images. Quality assessments are conducted both qualitatively through visual results and quantitatively using Root Mean Square Error (RMSE), Correlation Coefficient (CC), Spectral Angle Mapper (SAM), Erreur Relative Globale Adimensionnelle de Synthése (ERGAS), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Universal Image Quality Index (UIQI).
MAPPING AND MONITORING WETLANDS USING SENTINEL-2 SATELLITE IMAGERY
Authors: Kaplan G. , Avdan U.
Published: November 2017

Abstract. Mapping and monitoring of wetlands as one of the world`s most valuable natural resource has gained importance with the developed of the remote sensing techniques. This paper presents the capabilities of Sentinel-2 successfully launched in June 2015 for mapping and monitoring wetlands. For this purpose, three different approaches were used, pixel-based, object-based and index-based classification. Additional, for more successful extraction of wetlands, a combination of object-based and index-based method was proposed. It was proposed the use of object-based classification for extraction of the wetlands boundaries and the use of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) for classifying the contents within the wetlands boundaries. As a study area in this paper Sakarbasi spring in Eskisehir, Turkey was chosen. The results showed successful mapping and monitoring of wetlands with kappa coefficient of 0.95.
LIFE CYCLE DATA ANALYSIS FOR SMART CITIES AND SUPPORT WITH GEOGRAPHIC INFORMATION SYSTEM (GIS)
Authors: Kocalar A. C.
Published: November 2017

Abstract. The dynamics of globalization have gained momentum with today's developing technology. So we are now faced with the problems of urbanization (and urban governance), which become more evident than in the old days. As the subject cities, interdisciplinary qualities must always be considered. In the study, too, the focus of the urban area was on the problematic issue of intelligent or smart (especially, transportation) management that remained within this framework. GIS plays a major role in establishing the relationship between all kinds of analyses and visual information in the same environment and in determining the right strategies. For this reason, the use of GIS for decision makers is one of the most commonly used methods for intellectual production in the smart cities concept. The work to be done with this method will be able to be systematically successful and sustainable applications in this way.