A Cross-Sectional Survey on Knowledge and Perceptions of Health Risks Associated with Arsenic and Mercury Contamination from Artisanal Gold mining in Tanzania.

An estimated 0.5 to 1.5 million informal miners, of whom 30-50% are women, rely on artisanal mining for their livelihood in Tanzania. Mercury, used in the processing gold ore, and arsenic, which is a constituent of some ores, are common occupational exposures that frequently result in widespread environmental contamination. Frequently, the mining activities are conducted haphazardly without regard for environmental, occupational, or community exposure. The primary objective of this study was to assess community risk knowledge and perception of potential mercury and arsenic toxicity and/or exposure from artisanal gold mining in Rwamagasa in northwestern Tanzania. A cross-sectional survey of respondents in five sub-villages in the Rwamagasa Village located in Geita District in northwestern Tanzania near Lake Victoria was conducted. This area has a history of artisanal gold mining and many of the population continue to work as miners. Using a clustered random selection approach for recruitment, a total of 160 individuals over 18 years of age completed a structured interview. The interviews revealed wide variations in knowledge and risk perceptions concerning mercury and arsenic exposure, with 40.6% (n=65) and 89.4% (n=143) not aware of the health effects of mercury and arsenic exposure respectively. Males were significantly more knowledgeable (n=59, 36.9%) than females (n=36, 22.5%) with regard to mercury (x²=3.99, p<0.05). An individual's occupation category was associated with level of knowledge (x²=22.82, p=<0.001). Individuals involved in mining (n=63, 73.2%) were more knowledgeable about the negative health effects of mercury than individuals in other occupations. Of the few individuals (n=17, 10.6%) who knew about arsenic toxicity, the majority (n=10, 58.8%) were miners. The knowledge of individuals living in Rwamagasa, Tanzania, an area with a history of artisanal gold mining, varied widely with regard to the health hazards of mercury and arsenic. In these communities there was limited awareness of the threats to health associated with exposure to mercury and arsenic. This lack of knowledge, combined with minimal environmental monitoring and controlled waste management practices, highlights the need for health education, surveillance, and policy changes

SAFIRE borehole, AWS and GPS datasets

Datasets from the Subglacial Access and Fast Ice Research Experiment (SAFIRE) as published in the paper by Doyle et al. entitled "Physical conditions of fast glacier flow: 1. Measurements from boreholes drilled to the bed of Store Glacier, West Greenland". Please cite this paper if using this data. Citation below. Doyle, S.H., Hubbard, B., Christoffersen, P., Young, T. J., Hofstede, C., Bougamont, M., Box, J. E. & Hubbard, A. 2018. Physical conditions of fast glacier flow: 1. Measurements from boreholes drilled to the bed of Store Glacier, West Greenland, Journal of Geophysical Research: Earth Surface, DOI: 10.1002/2017JF004529. Field site: 30 km from the terminus of Store Glacier in West Greenland (N70° 31' W049° 55', 982 m asl). Contents 1. 2014_aws_timeseries.csv: Hourly time series of near surface air temperature, relative humidity and surface height made by an automated weather station (28 July 2014 to 21 October 2014). 2. 2016_aws_series.csv: As per dataset (1) for 2016 (12 July 2016 to 23 July 2016). 3. 2014_melt_timeseries.csv: Daily melt timeseries derived from the AWS measurements of surface height change for 2014 (29 July 2014 to 21 October 2014). 4. 2016_melt_timeseries.csv: As per dataset (3) for 2016 (12 July 2016 to 23 July 2016). 5. 2014_GPS_timeseries.csv: Timeseries of GPS surface height and velocity at a 30 second interval (3 August 2014 to 9 September 2014). 6. 2016_GPS_timeseries.csv: As per dataset (5) for 2016 (12 July 2016 to 22 July 2016). 7. 2014_thermistor_profile.csv: Ice temperature profile. 8. 2014_thermistor_timeseries.csv: Temperature time series from the thermistor string (27 July 2014 to 16 October 2014). 9. 2014_tilt_timeseries.csv: Timeseries from the tilt sensor string (27 July 2014 to 29 September 2014). 10. 2014_multiprobe_timeseries.csv: Timeseries of electrical conductivity, temperature, and pressure from the multi-sensor units (M1 and M2) installed in 2014 (28 July 2014 to 18 October 2014). 11. 2016_multiprobe_timeseries.csv: Time series of electrical conductivity, pressure and turbidity from the multi-sensor unit (M3) installed in 2016 (8 July 2016 to 22 July 2016). 12. 2014_drill_load_record_14b: Time series of load on the drill tower during the drilling of borehole 14b. 13. 2014_drill_load_record_14c: As per dataset (12) for the drilling of borehole 14c. 14. 2014_drill_load_record_14d: As per dataset (12) for the drilling of borehole 14d. 15. 2016_drill_load_record_16a: As per dataset (12) for the drilling of borehole 16a. 16. 2016_drill_load_record_16c: As per dataset (12) for the drilling of borehole 16c. 17. 2016_drill_full_record_16a: Timeseries of drill depth, load and speed for the drilling of borehole 16a. 18. 2016_drill_full_record_16c: As per dataset (17) for the drilling of borehole 16c. Please also see the companion paper by Hofstede et al.: Hofstede, C., Christoffersen, P., Hubbard, B., Doyle, S.H., Young, T.J., Diez, A., Eisen, O. & Hubbard, A. Physical conditions of fast glacier flow: 2. Variable extent of anisotropic ice and soft basal sediment from seismic reflection data acquired on Store Glacier, West Greenland, Journal of Geophysical Research: Earth Surface, DOI: 10.1002/2017JF004297

Starptautiskais seminars "Vides modelesana" Referati

In 2 vols.Available from Latvian Academic Library / LAL - Latvian Academic LibrarySIGLELVLatvi

UAV imagery over K-sector of the Greenland Ice Sheet on 8 August 2014

Digital imagery acquired by a Sony NEX-5N digital camera vertically mounted inside a fixed-wing UAV. The UAV surveyed a 25 km east-west transect dissecting the dark zone of the K-sector of the Greenland Ice Sheet on 8 August 2014. The camera has a 16 mm fixed focus lens (53.1 by 73.7° field of view) yielding an image footprint of approximately 525 x 350 m during the autonomous sortie. The camera was preset with a fixed shutter speed of 1/1000 s, ISO 100 and F-stop of 8. The images have a pixel footprint of approximately 11 cm. A corresponding csv file provides the UAV geolocation and attitude data for each image. The data were logged by an Arduino navigation and flight computer in real-time by a 10 Hz data stream comprising of a GPS, magnetometer, barometer and accelerometer

Before reliable near infrared spectroscopic analysis - the critical sampling proviso. Part 1. Generalised theory of sampling

Non-representative sampling of materials, lots and processes intended for near infrared (NIR) analysis is often contributing hidden additions to the full Measurement Uncertainty (MUtotal = TSE + TAENIR). The Total Sampling Error (TSE) can dominate over the Total Analytical Error (TAENIR) by factors ranging from 5 to 10 to even 25 times, depending on material heterogeneity and the specific sampling procedures employed to produce the minuscule aliquot, which is the only material analysed. This review (Parts 1 and 2), extensively referenced with easily available complementing literature, presents a brief of all sampling uncertainty elements in the “lot-to-aliquot” pathway, which must be identified and correctly managed (eliminated or maximally reduced) in order to achieve, and to be able to document, fully minimised MUtotal. The more irregular and pervasive the heterogeneity, the higher the number of increments needed to reach ‘fit-for-purpose representativity’. A particular focus is necessary regarding the sampling bias, which is fundamentally different from the well-known analytical bias. Whereas the latter can easily be subjected to bias correction, the sampling bias is non-correctable by any posteori means, notably not by chemometrics, nor statistics. Instead, all sampling operations must be designed to exclude the so-called Incorrect Sampling Errors (ISE), which are the hidden bias-generating agents. The key element in this endeavour is representative sampling and sub-sampling before analysis, as laid out by the Theory of Sampling (TOS), which is presented here in a novel compact fashion along with a complement of selected examples and demonstrations. TOS includes a safeguard facility, termed the Replication Experiment (RE), which enables estimation of the total sampling-plus-analysis uncertainty level (MUtotal) associated with NIR analysis (the RE is, for practical and logistical reasons, found in Part 2). Neglecting the TSE effects from the before-analysis domain is lack of due diligence. TOS to the fore

Before reliable near infrared spectroscopic analysis - the critical sampling proviso. Part 1. Generalised theory of sampling

Non-representative sampling of materials, lots and processes intended for near infrared (NIR) analysis is often contributing hidden additions to the full Measurement Uncertainty (MUtotal = TSE + TAENIR). The Total Sampling Error (TSE) can dominate over the Total Analytical Error (TAENIR) by factors ranging from 5 to 10 to even 25 times, depending on material heterogeneity and the specific sampling procedures employed to produce the minuscule aliquot, which is the only material analysed. This review (Parts 1 and 2), extensively referenced with easily available complementing literature, presents a brief of all sampling uncertainty elements in the “lot-to-aliquot” pathway, which must be identified and correctly managed (eliminated or maximally reduced) in order to achieve, and to be able to document, fully minimised MUtotal. The more irregular and pervasive the heterogeneity, the higher the number of increments needed to reach ‘fit-for-purpose representativity’. A particular focus is necessary regarding the sampling bias, which is fundamentally different from the well-known analytical bias. Whereas the latter can easily be subjected to bias correction, the sampling bias is non-correctable by any posteori means, notably not by chemometrics, nor statistics. Instead, all sampling operations must be designed to exclude the so-called Incorrect Sampling Errors (ISE), which are the hidden bias-generating agents. The key element in this endeavour is representative sampling and sub-sampling before analysis, as laid out by the Theory of Sampling (TOS), which is presented here in a novel compact fashion along with a complement of selected examples and demonstrations. TOS includes a safeguard facility, termed the Replication Experiment (RE), which enables estimation of the total sampling-plus-analysis uncertainty level (MUtotal) associated with NIR analysis (the RE is, for practical and logistical reasons, found in Part 2). Neglecting the TSE effects from the before-analysis domain is lack of due diligence. TOS to the fore

A revised stratigraphy for the Palaeocene Agatdalen flora (Nuussuaq Peninsula, western Greenland): correlating fossiliferous outcrops, macrofossils, and palynological samples from phosphoritic nodules

The Cretaceous and Palaeogene floras of western Greenland that were initially described as part of the classical work “Flora fossilis arctica” by Oswald Heer in the 19th century are currently under revision. The Nuussuaq Basin has repeatedly been investigated by geologists and marine invertebrate palaeontologists. These studies provide a modern stratigraphic framework and a basis for revisions of various Cretaceous to Eocene floras from this region, and the correlation of fossil material to stratigraphic units and formal formations. This paper is the first in a series of papers that (i) correlate macrofossil (museum) material and fossil-rich localities with the modern lithostratigraphic framework, (ii) describe new pollen, spores, and other marine/freshwater palynomorphs, and (iii) revise the macrofossil remains from the Agatdalen area (particularly the Danian Agatdal Formation). Since the work of B. Eske Koch in the 1960s and 70s, questions emerged about the correlation of plant fossiliferous outcrops and whether the so-called Agatdalen flora, referred to the Agatdal Formation, originates from a single sedimentary unit or not. In this paper, we summarise the stratigraphy of the Agatdalen area and correlate the fossil plant-bearing outcrops described by Koch to the current lithostratigraphy. We establish which plant fossils belong to the Agatdal Formation and re-assign a great number of other plant fossils to their correct formations. New palynological material is briefly described and correlated to the macrofossil localities and the Agatdal Formation. Previous accounts on the macrofossils (leaves, fruits, seeds) are briefly discussed and directions for future revisions are outlined

Rapid basal melting of the Greenland Ice Sheet from surface meltwater drainage (dataset)

Subglacial hydrologic systems regulate ice sheet flow, causing acceleration or deceleration, depending on hydraulic efficiency and the rate at which surface meltwater is delivered to the bed. Because these systems are rarely observed, ice sheet basal drainage represents a poorly integrated and uncertain component of models used to predict sea level changes. Dataset includes borehole data from a large Greenlandic outlet glacier

Rapid basal melting of the Greenland Ice Sheet from surface meltwater drainage (dataset)

Subglacial hydrologic systems regulate ice sheet flow, causing acceleration or deceleration, depending on hydraulic efficiency and the rate at which surface meltwater is delivered to the bed. Because these systems are rarely observed, ice sheet basal drainage represents a poorly integrated and uncertain component of models used to predict sea level changes. Dataset includes borehole data from a large Greenlandic outlet glacier