Comparison of Bulk, Wet-Only, and Wet-plus-Dry Deposition Measurements at the Turkey Lakes Watershed

1988 ◽  
Vol 45 (S1) ◽  
pp. s26-s37 ◽  
Author(s):  
Robert J. Vet ◽  
Alain Sirois ◽  
Dean S. Jeffries ◽  
R. G. Semkin ◽  
N. W. Foster ◽  
...  
Keyword(s):  
Atmospheric Deposition ◽  
Dry Deposition ◽  
Measurement Methods ◽  
Bulk Deposition ◽  
Data Sets ◽  
Bulk Data ◽  
Different Types ◽  
Turkey Lakes Watershed ◽  
Seasonal Deposition ◽  
Nitrate Deposition

Four different types of atmospheric deposition measurements were made at the Turkey Lakes Watershed from 1981 to 1984. They included weekly and variable period bulk deposition measurements. The resulting annual and seasonal deposition estimates from the four methods were compared for numerical and statistical differences. Several results unexpected from the theory of the measurement methods appeared in the comparison: (1) one of the bulk deposition measurements produced lower deposition of acid-related ions than the two wet-only measurements and (2) the monthly wet-only measurements produced higher deposition of sulphate than the two bulk deposition data sets (by 6 and 19%). Several results were consistent with the theory of the measurements: (1) the daily wet-only measurements produced deposition values lower than the weekly bulk deposition measurements and (2) the wet-plus-dry deposition measurements produced higher estimates of sulphate and nitrate deposition than the two bulk data sets (15 – 35% higher). Laboratory biases appeared to be partially responsible for some of the differences found in the comparison.

Detailed Analysis of Sulphate and Nitrate Atmospheric Deposition Estimates at the Turkey Lakes Watershed

1988 ◽  
Vol 45 (S1) ◽  
pp. s14-s25 ◽  
Author(s):  
Alain Sirois ◽  
Robert J. Vet
Keyword(s):  
Atmospheric Deposition ◽  
Dry Deposition ◽  
Measurement Data ◽  
Seasonal Cycles ◽  
Nitrogen Species ◽  
Wet And Dry Deposition ◽  
Total Deposition ◽  
Molar Basis ◽  
Daily Events ◽  
Turkey Lakes Watershed

Daily concentrations of sulphates and nitrates in air and precipitation were measured atthe Turkey Lakes Watershed from September 1980 until December 1984. The measurement data were used to estimate wet, dry, and total deposition of sulphates and nitrates to the watershed. Over the 4 yr, the annual values of total (wet plus dry) deposition ranged from 34 to 38 (± 15%) mmol∙m−2∙yr−1 for SO42− and from 38 to 47 (± 30%) mmol∙m−2∙yr−1 for NO3−. On a molar basis, the deposition of total NO3− exceeded the deposition of total SO42− by 19%. However, when converted to equivalents, total SO42− exceeded total NO3− by 68%. Dry deposition represented approximately 15 and 25% of the total deposition of SO42− and NO3−, respectively, to the watershed. Wet and dry deposition of sulphate and nitrate was found to be highly episodic, with the top 20% of daily events delivering 60–70% of the total sulphur and nitrogen deposition to the watershed. Statistically significant seasonal cycles were found in the concentration and deposition values of most of the sulphur and nitrogen species measured at the watershed.

Chemistry of Atmospheric Deposition, the Snowpack, and Snowmelt in the Turkey Lakes Watershed

1988 ◽  
Vol 45 (S1) ◽  
pp. s38-s46 ◽  
Author(s):  
R. G. Semkin ◽  
D. S. Jeffries
Keyword(s):  
Atmospheric Deposition ◽  
Dry Deposition ◽  
Major Ions ◽  
Chemical Fractionation ◽  
Northern Ontario ◽  
Lake Chemistry ◽  
Total Deposition ◽  
Bulk Sampler ◽  
Turkey Lakes Watershed ◽  
Lake Waters

Bulk and wet-only deposition and the snowpack were monitored at the Turkey Lakes Watershed in northern Ontario over the winter and spring of 1986. Based on a comparison with snowpack and cumulative snowmelt, the bulk sampler overcollected major ions by factors ranging from 6 to 22%. Nitrate appeared to be preferentially collected by the bulk sampler relative to SO42− during snow events. Dry deposition was estimated to be 12 and 5% of total deposition forSO42− and NO3−, respectively. Ion budgets for cumulative bulk deposition and snowmelt supported the hypothesis that ion losses from the snowpack are insignificant during a winter having no melt episodes. Snowmelt was characterized by chemical fractionation of major ions; SO42− and H+ in initial meltwaters were 10 times more concentrated than the premelt snowpack. Preferential elution of ions in the snowmelt followed the sequence: SO42− > NO3− > H+ > Cl−. Snowmelt chemistry was used to predict changes in lake chemistry: H+, NO3−, and NH4+ levels should increase in lake waters; Ca2+ decreases through dilution by snowmelt; SO42− concentrations remain fairly constant.

scholarly journals Triple oxygen isotopes indicate urbanization affects sources of nitrate in wet and dry atmospheric deposition

2018 ◽  
Author(s):  
David M. Nelson ◽  
Urumu Tsunogai ◽  
Ding Dong ◽  
Takuya Ohyama ◽  
Daisuke D. Komatsu ◽  
...  
Keyword(s):  
Dry Deposition ◽  
Wet Deposition ◽  
Urban Environments ◽  
Rural Site ◽  
Urban Site ◽  
Peroxy Radicals ◽  
Long Distance ◽  
Wet And Dry Deposition ◽  
Atmospheric Nitrate ◽  
Nitrate Deposition

Abstract. Atmospheric nitrate deposition resulting from anthropogenic activities negatively affects human and environmental health. Identifying deposited nitrate that is produced locally vs. that originating from long-distance transport would help inform efforts to mitigate such impacts. However, distinguishing the relative transport distances of atmospheric nitrate in urban areas remains a major challenge since it may be produced locally and/or come from upwind regions. To address this uncertainty we assessed spatiotemporal variation in monthly weighted-average Δ17O and δ15N values of wet and dry nitrate deposition during one year at urban and rural sites along the western coast of the northern Japanese island of Hokkaido, downwind of the East Asian continent. Δ17O values of nitrate in wet deposition at the urban site mirrored those of wet and dry deposition at the rural site, ranging between ~ +22 and +30 ‰ with higher values during winter and lower values in summer, which suggests greater relative importance of oxidation of NO2 by O3 during winter and OH during summer. In contrast, Δ17O values of nitrate in dry deposition at the urban site were lower (+19–+25 ‰) and displayed less distinct seasonal variation. Furthermore, the difference between δ15N values of nitrate in wet and dry nitrate deposition was, on average, 3 ‰ greater at the urban than rural site, and Δ17O and δ15N values were correlated for both forms of deposition at both sites with the exception of dry deposition at the urban site. These results suggest that, relative to nitrate in wet deposition in urban environments and wet and dry deposition in rural environments, nitrate in dry deposition in urban environments forms from relatively greater oxidation of NO by peroxy radicals and/or oxidation of NO2 by OH. Given greater concentrations of peroxy radicals and OH in cities, these results imply that dry nitrate deposition results from local NOx emissions more so than wet deposition, which is transported longer distances. These results illustrate the value of stable isotope data for distinguishing the transport distances and reaction pathways of atmospheric nitrate pollution.

scholarly journals Temporal and Spatial variation of Contribution from Ship Emissions to the concentration and deposition of air pollutants in the Baltic Sea

2016 ◽  
Author(s):  
Karin Haglund ◽  
Björn Claremar ◽  
Anna Rutgersson
Keyword(s):  
Atmospheric Deposition ◽  
Baltic Sea ◽  
Dry Deposition ◽  
Air Pollutants ◽  
Wet Deposition ◽  
Sulphur Content ◽  
The Baltic Sea ◽  
Near Surface ◽  
Baltic Sea Region ◽  
The Baltic

Abstract. The shipping sector contributes significantly to increasing emissions of air pollutants. In order to achieve sustainable shipping, primarily through new regulations and techniques, greater knowledge of dispersion and deposition of air pollutants is required. Regional model calculations of the dispersion and deposition of sulphur, nitrogen and particulate matter from the international maritime sector in the Baltic Sea and the North Sea have been made for the years 2009 to 2013. In some areas in the Baltic Sea region the contribution of sulphur dioxide, nitrogen oxide and nitrogen dioxide from international shipping represented up to 80 % of the total near surface concentration of the pollutants. Contributions from shipping of PM2,5 and PM10 were calculated to a maximum of 21 % and 13 % respectively. The contribution of wet deposition of sulphur from shipping was maximum 29 % of the total wet deposition, and for dry deposition the contribution from shipping was maximum 84 %. The highest percentage contribution of wet deposition of nitrogen from shipping reached 28 % and for dry deposition 47 %. The highest concentrations and deposition of the pollutants in the study were found near large ports and shipping lanes. High concentrations were also found over larger areas at sea and over land where many people are exposed. With enhanced regulations for sulphur content in maritime fuel, the cleaning of exhausts through scrubbers has become a possible economic solution. Wet scrubbers meet the air quality criteria but their consequences for the marine environment are largely unknown. The resulting potential of future acidification in the Baltic Sea, both from atmospheric deposition and from open-loop scrubber water along the shipping lanes, based on different assumptions about sulphur content in fuel and scrubber usage has been assessed. Shipping is expected to increase globally and in the Baltic Sea region, deposition of sulphur due to shipping will depend on traffic density, emission regulations and technology choices for the emission controls. To evaluate future changes scenarios are developed considering the amount of scrubber technology used. The increase in deposition for the different scenarios differs slightly for the basins in the Baltic Sea. The proportion of ocean acidifying sulphur from ships increases when taking scrubber water into account and the major reason to increasing acidifying nitrogen from ships are due to increasing ship traffic. This study also generates a database of scenarios for atmospheric deposition and scrubber exhaust from the period 2011 to 2050.

scholarly journals Machine learning for improved data analysis of biological aerosol using the WIBS

2018 ◽  
Vol 11 (11) ◽  
pp. 6203-6230 ◽  
Author(s):  
Simon Ruske ◽  
David O. Topping ◽  
Virginia E. Foot ◽  
Andrew P. Morse ◽  
Martin W. Gallagher
Keyword(s):  
Ultraviolet Light ◽  
Fungal Spores ◽  
Laboratory Data ◽  
Misclassification Rate ◽  
Gradient Boosting ◽  
Classification Error ◽  
Data Sets ◽  
Data Preparation ◽  
Different Types ◽  
Selection Of

Abstract. Primary biological aerosol including bacteria, fungal spores and pollen have important implications for public health and the environment. Such particles may have different concentrations of chemical fluorophores and will respond differently in the presence of ultraviolet light, potentially allowing for different types of biological aerosol to be discriminated. Development of ultraviolet light induced fluorescence (UV-LIF) instruments such as the Wideband Integrated Bioaerosol Sensor (WIBS) has allowed for size, morphology and fluorescence measurements to be collected in real-time. However, it is unclear without studying instrument responses in the laboratory, the extent to which different types of particles can be discriminated. Collection of laboratory data is vital to validate any approach used to analyse data and ensure that the data available is utilized as effectively as possible. In this paper a variety of methodologies are tested on a range of particles collected in the laboratory. Hierarchical agglomerative clustering (HAC) has been previously applied to UV-LIF data in a number of studies and is tested alongside other algorithms that could be used to solve the classification problem: Density Based Spectral Clustering and Noise (DBSCAN), k-means and gradient boosting. Whilst HAC was able to effectively discriminate between reference narrow-size distribution PSL particles, yielding a classification error of only 1.8 %, similar results were not obtained when testing on laboratory generated aerosol where the classification error was found to be between 11.5 % and 24.2 %. Furthermore, there is a large uncertainty in this approach in terms of the data preparation and the cluster index used, and we were unable to attain consistent results across the different sets of laboratory generated aerosol tested. The lowest classification errors were obtained using gradient boosting, where the misclassification rate was between 4.38 % and 5.42 %. The largest contribution to the error, in the case of the higher misclassification rate, was the pollen samples where 28.5 % of the samples were incorrectly classified as fungal spores. The technique was robust to changes in data preparation provided a fluorescent threshold was applied to the data. In the event that laboratory training data are unavailable, DBSCAN was found to be a potential alternative to HAC. In the case of one of the data sets where 22.9 % of the data were left unclassified we were able to produce three distinct clusters obtaining a classification error of only 1.42 % on the classified data. These results could not be replicated for the other data set where 26.8 % of the data were not classified and a classification error of 13.8 % was obtained. This method, like HAC, also appeared to be heavily dependent on data preparation, requiring a different selection of parameters depending on the preparation used. Further analysis will also be required to confirm our selection of the parameters when using this method on ambient data. There is a clear need for the collection of additional laboratory generated aerosol to improve interpretation of current databases and to aid in the analysis of data collected from an ambient environment. New instruments with a greater resolution are likely to improve on current discrimination between pollen, bacteria and fungal spores and even between different species, however the need for extensive laboratory data sets will grow as a result.

scholarly journals SATzilla: Portfolio-based Algorithm Selection for SAT

2008 ◽  
Vol 32 ◽  
pp. 565-606 ◽  
Author(s):  
L. Xu ◽  
F. Hutter ◽  
H. H. Hoos ◽  
K. Leyton-Brown
Keyword(s):  
Traditional Approach ◽  
Data Sets ◽  
Algorithm Selection ◽  
New Techniques ◽  
Algorithm Portfolios ◽  
Predicting Performance ◽  
Different Types ◽  
Sat Solver ◽  
Selection For ◽  
Problem Instances

It has been widely observed that there is no single "dominant" SAT solver; instead, different solvers perform best on different instances. Rather than following the traditional approach of choosing the best solver for a given class of instances, we advocate making this decision online on a per-instance basis. Building on previous work, we describe SATzilla, an automated approach for constructing per-instance algorithm portfolios for SAT that use so-called empirical hardness models to choose among their constituent solvers. This approach takes as input a distribution of problem instances and a set of component solvers, and constructs a portfolio optimizing a given objective function (such as mean runtime, percent of instances solved, or score in a competition). The excellent performance of SATzilla was independently verified in the 2007 SAT Competition, where our SATzilla07 solvers won three gold, one silver and one bronze medal. In this article, we go well beyond SATzilla07 by making the portfolio construction scalable and completely automated, and improving it by integrating local search solvers as candidate solvers, by predicting performance score instead of runtime, and by using hierarchical hardness models that take into account different types of SAT instances. We demonstrate the effectiveness of these new techniques in extensive experimental results on data sets including instances from the most recent SAT competition.

Digital Bookstore

2021 ◽  
Vol 9 (VII) ◽  
pp. 1326-1337
Author(s):  
Amey Thakur
Keyword(s):  
Programming Languages ◽  
Web Application ◽  
Credit Card ◽  
Sql Server ◽  
Data Sets ◽  
Frequent User ◽  
Web Browser ◽  
Book Store ◽  
Different Types ◽  
Online Book

The project's main goal is to build an online book store where users can search for and buy books based on title, author, and subject. The chosen books are shown in a tabular style and the customer may buy them online using a credit card. Using this Website, the user may buy a book online rather than going to a bookshop and spending time. Many online bookstores, such as Powell's and Amazon, were created using HTML. We suggest creating a comparable website with .NET and SQL Server. An online book store is a web application that allows customers to purchase ebooks. Through a web browser the customers can search for a book by its title or author, later can add it to the shopping cart and finally purchase using a credit card transaction. The client may sign in using his login credentials, or new clients can simply open an account. Customers must submit their full name, contact details, and shipping address. The user may also provide a review of a book by rating it on a scale of one to five. The books are classified into different types depending on their subject matter, such as software, databases, English, and architecture. Customers can shop online at the Online Book Store Website using a web browser. A client may create an account, sign in, add things to his shopping basket, and buy the product using his credit card information. As opposed to a frequent user, the Administrator has more abilities. He has the ability to add, delete, and edit book details, book categories, and member information, as well as confirm a placed order. This application was created with PHP and web programming languages. The Online Book Store is built using the Master page, data sets, data grids, and user controls.

scholarly journals Plant assemblages in atmospheric deposition

2019 ◽  
Author(s):  
Ke Dong ◽  
Cheolwoon Woo ◽  
Naomichi Yamamoto
Keyword(s):  
Atmospheric Deposition ◽  
Dry Deposition ◽  
Wet Deposition ◽  
High Throughput Sequencing ◽  
Sampling Site ◽  
Its2 Region ◽  
Dry And Wet Deposition ◽  
Custom Made ◽  
Plant Assemblages ◽  
Cloud Scavenging

Abstract. Plants disperse spores, pollen, and fragments into the atmosphere. The emitted plant particles return to the pedosphere by sedimentation (dry deposition) and/or by precipitation (wet deposition) and constitute part of the global cycle of substances. However, little is known regarding the taxonomic diversities and flux densities of plant particles deposited from the atmosphere. Here, plant assemblages were examined in atmospheric deposits collected in Seoul in South Korea. A custom-made automatic sampler was used to collect dry and wet deposition samples for which plant assemblages and quantities were determined using high-throughput sequencing and quantitative PCR with universal plant-specific primers targeting the internal transcribed spacer 2 (ITS2) region. Dry deposition was dominant for atmospheric deposition of plant particles (87 %). The remaining 13 % was deposited by precipitation, i.e., wet deposition, via rainout (in-cloud scavenging) and/or washout (below-cloud scavenging). Plant assemblage structures did not differ significantly between dry and wet deposition, indicating that washout, which is likely taxon-independent, predominated rainout, which is likely taxon-dependent, for wet deposition of atmospheric plant particles. A small number of plant genera were detected only in wet deposition, indicating that they might be specifically involved in precipitation through acting as nucleation sites in the atmosphere. Future interannual monitoring will control for the seasonality of atmospheric plant assemblages observed at our sampling site. Future global monitoring is also proposed to investigate geographical differences and investigate whether endemic species are involved in plant-mediated bioprecipitation in regional ecological systems.

scholarly journals Impact of dust deposition on carbon budget: a tentative assessment from a mesocosm approach

2014 ◽  
Vol 11 (19) ◽  
pp. 5621-5635 ◽  
Author(s):  
C. Guieu ◽  
C. Ridame ◽  
E. Pulido-Villena ◽  
M. Bressac ◽  
K. Desboeufs ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Atmospheric Deposition ◽  
Mediterranean Sea ◽  
Particulate Organic Carbon ◽  
Dry Deposition ◽  
Wet Deposition ◽  
Carbon Budget ◽  
Net Primary Production ◽  
Saharan Dust ◽  
Dust Deposition

Abstract. By bringing new nutrients and particles to the surface ocean, atmospheric deposition impacts biogeochemical cycles. The extent to which those changes are modifying the carbon balance in oligotrophic environments such as the Mediterranean Sea that receives important Saharan dust fluxes is unknown. The DUNE (DUst experiment in a low Nutrient, low chlorophyll Ecosystem) project provides the first attempt to evaluate the changes induced in the carbon budget of a large body of oligotrophic waters after simulated Saharan dust wet or dry deposition events, allowing us to measure (1) the metabolic fluxes while the particles are sinking and (2) the particulate organic carbon export. Here we report the results for the three distinct artificial dust seeding experiments simulating wet or dry atmospheric deposition onto large mesocosms (52 m3) that were conducted in the oligotrophic waters of the Mediterranean Sea in the summers of 2008 and 2010. Although heterotrophic bacteria were found to be the key players in the response to dust deposition, net primary production increased about twice in case of simulated wet deposition (that includes anthropogenic nitrogen). The dust deposition did not produce a shift in the metabolic balance as the tested waters remained net heterotrophic (i.e., net primary production to bacteria respiration ratio <1) and in some cases the net heterotrophy was even enhanced by the dust deposition. The change induced by the dust addition on the total organic carbon pool inside the mesocosm over the 7 days of the experiments, was a carbon loss dominated by bacteria respiration that was at least 5–10 times higher than any other term involved in the budget. This loss of organic carbon from the system in all the experiments was particularly marked after the simulation of wet deposition. Changes in biomass were mostly due to an increase in phytoplankton biomass but when considering the whole particulate organic carbon pool it was dominated by the organic carbon aggregated to the lithogenic particles still in suspension in the mesocosm at the end of the experiment. Assuming that the budget is balanced, the dissolved organic carbon (DOC) pool was estimated by the difference between the total organic carbon and the particulate organic carbon (POC) pool. The partitioning between dissolved and particulate organic carbon was dominated by the dissolved pool with a DOC consumption over 7 days of ∼1 μmol C L−1 d−1 (dry deposition) to ∼2–5 μmol C L−1 d−1 (wet deposition). This consumption in the absence of any allochthonous inputs in the closed mesocosms meant a small <10% decrease of the initial DOC stock after a dry deposition but a ∼30–40% decrease of the initial DOC stock after wet deposition. After wet deposition, the tested waters, although dominated by heterotrophy, were still maintaining a net export (corrected from controls) of particulate organic carbon (0.5 g in 7 days) even in the absence of allochthonous carbon inputs. This tentative assessment of the changes in carbon budget induced by a strong dust deposition indicates that wet deposition by bringing new nutrients has higher impact than dry deposition in oligotrophic environments. In the western Mediterranean Sea, the mineral dust deposition is dominated by wet deposition and one perspective of this work is to extrapolate our numbers to time series of deposition during similar oligotrophic conditions to evaluate the overall impact on the carbon budget at the event and seasonal scale in the surface waters of the northwestern Mediterranean Sea. These estimated carbon budgets are also highlighting the key processes (i.e., bacterial respiration) that need to be considered for an integration of atmospheric deposition in marine biogeochemical modeling.

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