A review of bioconcentration factor (BCF) and bioaccumulation factor (BAF) assessments for organic chemicals in aquatic organisms

2006 ◽  
Vol 14 (4) ◽  
pp. 257-297 ◽  
Author(s):  
Jon A Arnot ◽  
Frank APC Gobas
Keyword(s):  
Measurement Errors ◽  
Bioconcentration Factor ◽  
Model Development ◽  
Critical Evaluation ◽  
Aquatic Organisms ◽  
Bioaccumulation Factor ◽  
Quality Data ◽  
Organic Chemicals ◽  
Reliable Assessment ◽  
The Status

Bioaccumulation assessment is important in the scientific evaluation of risks that chemicals may pose to humans and the environment and is a current focus of regulatory effort. The status of bioaccumulation evaluations for organic chemicals in aquatic systems is reviewed to reduce uncertainty in bioaccumulation measurement, to provide quality data for assessment, and to assist in model development. A review of 392 scientific literature and database sources includes 5317 bioconcentration factor (BCF) and 1656 bioaccumulation factor (BAF) values measured for 842 organic chemicals in 219 aquatic species. A data quality assessment finds that 45% of BCF values are subject to at least one major source of uncertainty and that measurement errors generally result in an underestimation of actual BCF values. A case study of organic chemicals on the Canadian Domestic Substances List indicates that empirical data are available for less than 4% of the chemicals that require evaluation and of these chemicals, 76% have less than three acceptable quality BCF or BAF values. Field BAFs tend to be greater than laboratory BCFs emphasizing the importance of environmental measurement for reliable assessment; however, only 0.2% of current use organic chemicals have BAF measurements. Key parameters influencing uncertainty and variability in BCF and BAF data are discussed using reviewed data and models. A critical evaluation of representative BCF and BAF models in relation to existing measurements and regulatory criteria in Canada indicate the probability of Type II errors, i.e., false negatives or ``misses'', using BCF models for bioaccumulation assessment may be as high as 70.6% depending on the model. Recommendations for the selection of measured and modelled values used in bioaccumulation assessment are provided, and improvements for the science and regulatory criteria are proposed.Key words: bioconcentration, bioconcentration factor, bioaccumulation, bioaccumulation factor, octanol–water partition coefficient, fish.

Factors Affecting Bioconcentration of Trace Organic Contamination in Waters

1989 ◽  
Vol 21 (2) ◽  
pp. 147-150 ◽  
Author(s):  
D. W. Hawker ◽  
D. W. Connell
Keyword(s):  
Molecular Weight ◽  
Bioconcentration Factor ◽  
Aqueous Solubility ◽  
Organic Chemicals ◽  
Organic Contamination ◽  
Hydrophobic Organic Chemicals ◽  
Factors Affecting ◽  
Water Partition Coefficient ◽  
Physicochemical Factors ◽  
Trace Organic

The influence of some important biological and physicochemical factors on the bioconcentration of hydrophobic organic chemicals is outlined. For non-ionizable, persistent compounds the bioconcentration factor can be related to a compound's octanol/water partition coefficient, aqueous solubility and molecular weight, while the lipid content of an organism also affects the bioconcentration potential of these compounds. The effect of ionization and biodegradation of organic chemicals on bioconcentration is also discussed.

Collecting High-Quality Data

2018 ◽  
Author(s):  
Mary Kay Gugerty ◽  
Dean Karlan
Keyword(s):  
Data Collection ◽  
Social Desirability ◽  
Measurement Errors ◽  
Monitoring And Evaluation ◽  
Quality Data ◽  
Social Desirability Bias ◽  
High Quality ◽  
High Quality Data ◽  
Evaluation Systems ◽  
Demand Effect

Without high-quality data, even the best-designed monitoring and evaluation systems will collapse. Chapter 7 introduces some the basics of collecting high-quality data and discusses how to address challenges that frequently arise. High-quality data must be clearly defined and have an indicator that validly and reliably measures the intended concept. The chapter then explains how to avoid common biases and measurement errors like anchoring, social desirability bias, the experimenter demand effect, unclear wording, long recall periods, and translation context. It then guides organizations on how to find indicators, test data collection instruments, manage surveys, and train staff appropriately for data collection and entry.

scholarly journals Modeling Building Stock Development

2021 ◽  
Vol 13 (2) ◽  
pp. 723
Author(s):  
Antti Kurvinen ◽  
Arto Saari ◽  
Juhani Heljo ◽  
Eero Nippala
Keyword(s):  
Model Development ◽  
Housing Demand ◽  
Quality Data ◽  
Building Stock ◽  
Test Arena ◽  
Climate Targets ◽  
Wide Range ◽  
Key Variables ◽  
The Impact

It is widely agreed that dynamics of building stocks are relatively poorly known even if it is recognized to be an important research topic. Better understanding of building stock dynamics and future development is crucial, e.g., for sustainable management of the built environment as various analyses require long-term projections of building stock development. Recognizing the uncertainty in relation to long-term modeling, we propose a transparent calculation-based QuantiSTOCK model for modeling building stock development. Our approach not only provides a tangible tool for understanding development when selected assumptions are valid but also, most importantly, allows for studying the sensitivity of results to alternative developments of the key variables. Therefore, this relatively simple modeling approach provides fruitful grounds for understanding the impact of different key variables, which is needed to facilitate meaningful debate on different housing, land use, and environment-related policies. The QuantiSTOCK model may be extended in numerous ways and lays the groundwork for modeling the future developments of building stocks. The presented model may be used in a wide range of analyses ranging from assessing housing demand at the regional level to providing input for defining sustainable pathways towards climate targets. Due to the availability of high-quality data, the Finnish building stock provided a great test arena for the model development.

scholarly journals Deep Learning-Based Cattle Vocal Classification Model and Real-Time Livestock Monitoring System with Noise Filtering

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 357
Author(s):  
Dae-Hyun Jung ◽  
Na Yeon Kim ◽  
Sang Ho Moon ◽  
Changho Jhin ◽  
Hak-Jin Kim ◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Model Development ◽  
Classification Model ◽  
Intelligence Analysis ◽  
Noise Filtering ◽  
Meat Industry ◽  
Mel Frequency Cepstral Coefficients ◽  
Web Based ◽  
The Status

The priority placed on animal welfare in the meat industry is increasing the importance of understanding livestock behavior. In this study, we developed a web-based monitoring and recording system based on artificial intelligence analysis for the classification of cattle sounds. The deep learning classification model of the system is a convolutional neural network (CNN) model that takes voice information converted to Mel-frequency cepstral coefficients (MFCCs) as input. The CNN model first achieved an accuracy of 91.38% in recognizing cattle sounds. Further, short-time Fourier transform-based noise filtering was applied to remove background noise, improving the classification model accuracy to 94.18%. Categorized cattle voices were then classified into four classes, and a total of 897 classification records were acquired for the classification model development. A final accuracy of 81.96% was obtained for the model. Our proposed web-based platform that provides information obtained from a total of 12 sound sensors provides cattle vocalization monitoring in real time, enabling farm owners to determine the status of their cattle.

Dialectic in the Hands of a Handwerker: Joseph Dietzgen and the Humble Beginnings of Dialectical Materialism

2021 ◽  
Vol 85 (3) ◽  
pp. 360-384
Author(s):  
Eric-John Russell
Keyword(s):  
Critical Evaluation ◽  
Dialectical Materialism ◽  
Natural Sciences ◽  
Dialectical Method ◽  
Human Thought ◽  
Marxist Ideology ◽  
The Status ◽  
German Worker ◽  
Materialist Dialectic

Engels once remarked to Marx that the “materialist dialectic, which for years has been our best working tool and our sharpest weapon, was, remarkably enough, discovered not only by us but also, independently of us and even of Hegel, by a German worker, Joseph Dietzgen.” The status of the dialectic, however, within what ought to instead be described as Dietzgen's inductive empiricism, is problematic. Dietzgen's work stands as a hitherto unacknowledged precursor to the Marxist ideology of Diamat. The first question is whether or not Marx's materialism ought to be conflated with Dietzgen's empiricism. Second, Dietzgen's efforts to establish a theory of human thought structured through the methods of the natural sciences requires critical evaluation. Although Dietzgen's works may anticipate some of the theoretical contours of Diamat, equating materialism with empiricism and rendering the dialectical method into a universal methodology on a par with the methods of the natural sciences, as pursued by Dietzgen, is a project that is perhaps not worthy of Marx's and Engels’ nominal veneration.

scholarly journals Data Beyond the Archive in Digital Archaeology

2018 ◽  
Vol 6 (2) ◽  
pp. 89-92 ◽  
Author(s):  
Sarah Whitcher Kansa ◽  
Eric C. Kansa
Keyword(s):  
Data Management ◽  
Special Section ◽  
Digital Data ◽  
Quality Data ◽  
Annual Conference ◽  
Archaeological Practice ◽  
Archaeological Data ◽  
The Status ◽  
Digital Archaeology ◽  
Virtuous Cycle

ABSTRACTThis special section stems from discussions that took place in a forum at the Society for American Archaeology's annual conference in 2017. The forum, Beyond Data Management: A Conversation about “Digital Data Realities”, addressed challenges in fostering greater reuse of the digital archaeological data now curated in repositories. Forum discussants considered digital archaeology beyond the status quo of “data management” to better situate the sharing and reuse of data in archaeological practice. The five papers for this special section address key themes that emerged from these discussions, including: challenges in broadening data literacy by making instructional uses of data; strategies to make data more visible, better cited, and more integral to peer-review processes; and pathways to create higher-quality data better suited for reuse. These papers highlight how research data management needs to move beyond mere “check-box” compliance for granting requirements. The problems and proposed solutions articulated by these papers help communicate good practices that can jumpstart a virtuous cycle of better data creation leading to higher impact reuses of data.

Chemical Determinands of Freshwater Ecosystem Functioning

2018 ◽  
pp. 89-105
Author(s):  
Nic Pacini ◽  
Libor Pechar ◽  
David M. Harper
Keyword(s):  
Major Ions ◽  
Chemical Interaction ◽  
Chemical Constituents ◽  
Measurement Techniques ◽  
Aquatic Organisms ◽  
Quality Data ◽  
Sample Collection ◽  
Intrinsic Variability ◽  
Chemical Monitoring ◽  
Run Off

Chemical equilibria in surface waters stem from complex interactions between physical background and living components of ecosystems. Catchments differ in geological background, climate, and land use; their run-off bears a distinctive chemical ‘fingerprint’. This chapter illustrates how the monitoring of standard parameters, such as oxygen, pH, conductivity, major ions, nutrients, and carbon, can lead to an interpretation of key aspects of the functioning of major ecosystem processes and how chemical constituents may affect the distribution of aquatic organisms. This requires understanding principles that underlie available measurement techniques and it demands a certain familiarity with the intrinsic variability of parameter values and of their chemical interaction. It is not required that field scientists be able to conduct detailed chemical assessments, but all should be able to collect samples yielding high-quality data. Therefore, detailed advice on chemical monitoring practice is provided, including sample collection, filtering, sample processing, and is discussed with the context of several case studies.

scholarly journals An Overview of the Science Performances and Calibration/Validation of Joint Polar Satellite System Operational Products

2019 ◽  
Vol 11 (6) ◽  
pp. 698 ◽  
Author(s):  
Lihang Zhou ◽  
Murty Divakarla ◽  
Xingpin Liu ◽  
Arron Layns ◽  
Mitch Goldberg
Keyword(s):  
Performance Monitoring ◽  
Performance Metrics ◽  
Satellite System ◽  
Quality Data ◽  
Direct Result ◽  
Science Data ◽  
Successful Operation ◽  
Data Products ◽  
The Status ◽  
Polar Satellite

The Suomi National Polar-orbiting Partnership (S-NPP) satellite, launched in October 2011, initiated a series of the next-generation weather satellites for the National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS) program. The JPSS program at the Center for Satellite Applications and Research (JSTAR) leads the development of the algorithms, the calibration and validation of the products to meet the specified requirements, and long-term science performance monitoring and maintenance. All of the S-NPP products have been validated and are in successful operation. The recently launched JPSS-1 (renamed as NOAA-20) satellite is producing high-quality data products that have been available from S-NPP, along with additional products, as a direct result of the instrument upgrades and science improvements. This paper presents an overview of the JPSS product suite, the performance metrics achieved for the S-NPP, and the utilization of the products by NOAA stakeholders and user agencies worldwide. The status of NOAA-20 science data products and ongoing calibration/validation (Cal/Val) efforts are discussed for user awareness. In addition, operational implementation statuses of JPSS enterprise (multisensor and multiplatform) science algorithms for product generation and science product reprocessing efforts for the S-NPP mission are discussed.

scholarly journals Snow and ice applications of AVHRR in polar regions: report of a workshop held in Boulder, Colorado, 20 May 1992

1993 ◽  
Vol 17 ◽  
pp. 1-16 ◽  
Author(s):  
K. Steffen ◽  
R. Bindschadler ◽  
G. Casassa ◽  
J. Comiso ◽  
D. Eppler ◽  
...  
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Quality Data ◽  
Polar Regions ◽  
Data Set ◽  
Ice Surface ◽  
The Status ◽  
Ice Surface Temperature ◽  
Snow And Ice

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17–22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

scholarly journals Critical evaluation of stability constants of metal complexes of complexones for biomedical and environmental applications* (IUPAC Technical Report)

2005 ◽  
Vol 77 (8) ◽  
pp. 1445-1495 ◽  
Author(s):  
Giorgio Anderegg ◽  
Francoise Arnaud-Neu ◽  
Rita Delgado ◽  
Judith Felcman ◽  
Konstantin Popov
Keyword(s):  
Experimental Data ◽  
Stability Constant ◽  
Metal Complexes ◽  
Stability Constants ◽  
Critical Evaluation ◽  
Iminodiacetic Acid ◽  
Quality Data ◽  
Tetraacetic Acid ◽  
Diacetic Acid ◽  
Technical Report

Available experimental data on stability constants of proton (hydron) and metal complexes for seven complexones of particular biomedical and environmental interest: iminodiacetic acid [2,2'-azanediyldiacetic acid, IDA], (methylimino)diacetic acid [2,2'-(methylazanediyl)diacetic acid, MIDA]; 2,2',2'',2'''-{[(carboxymethyl)azanediyl]bis[(ethane-1,2-diyl)nitrilo]}tetraacetic acid (DTPA), 3,6,9,12-tetrakis(carboxymethyl)-3,6,9,12-tetraazatetradecanedioic acid (TTHA); 2,2',2''-(1,4,7-triazonane-1,4,7-triyl)triacetic acid (NOTA); 2,2',2'',2'''-(1,4,7,10-tetraazacyclododecane-1,4,7,10-tetrayl)tetraacetic acid (DOTA); 2,2',2'',2'''-(1,4,8,11-tetraazacyclotetradecane-1,4,8,11-tetrayl)tetraacetic acid (TETA), published in 1945-2000, have been critically evaluated. Some typical errors in stability constant measurements for particular complexones are summarized. Higher quality data are selected and presented as “Recommended” or “Provisional”.

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