SEGH Events

30th SEGH Conference

30 June 2014
Newcastle, UK
Northumbria University, Newcastle-upon-Tyne, UK. 30th June to 4th July 2014 International Conference of the Society for Environmental Geochemistry and Health

Dear colleagues,

On behalf of the Organizing Committee of the 30th International SEGH conference (European Section), I would like to extend a warm welcome and invite you to join us at Northumbria University, Newcastle-upon-Tyne, UK, 30th June – 4th July, 2014.

This annual conference of the Society for Environmental Geochemistry and Health provides a forum for international scientists, consultants, regulatory authorities and other practitioners (public health / environmental health) with an interest in the links between environment and health and working in the broad area of environmental geochemistry. For the 30thSEGH we are keen to receive contributions on three core themes and two special sessions:

  •           Theme 1 - Chemical bioavailability and bioaccessibility
  •           Theme 2 - Risk Assessment, environmental exposure and health
  •           Theme 3 - Air & dust pollution and human health
  •           Special Session 1 - ‘Hydraulic Fracturing (Fracking) and Health’
  •           Special Session 2 - ‘Environmental iodine and the deficiency disorders’

We would also welcome submission of papers for any topics relevant to the aims of the Society.


The conference venue is the city campus of Northumbria University, in the heart of the city of Newcastle-upon-Tyne, North-East England, UK.


Abstract submission will open on December 2nd, 2013.

Abstract submission deadline is March 3rd, 2014


For further details please click here


Please save these key dates in your diary. More information will follow...

We look forward to welcoming you to Newcastle in 2014.


Best Regards,

Jane Entwistle [SEGH 2014 Chair]


Photographs courtesy of John Tan, Northumbria University


Dr Jane Entwistle

Head of Department,


Northumbria University

Newcastle upon Tyne


Tel: 00 44 (0)191 227 3017  e-mail:

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Science in the News

Latest on-line papers from the SEGH journal: Environmental Geochemistry and Health

  • Mechanistic understanding of crystal violet dye sorption by woody biochar: implications for wastewater treatment 2017-08-17


    Dye-based industries, particularly small and medium scale, discharge their effluents into waterways without treatment due to cost considerations. We investigated the use of biochars produced from the woody tree Gliricidia sepium at 300 °C (GBC300) and 500 °C (GBC500) in the laboratory and at 700 °C from a dendro bioenergy industry (GBC700), to evaluate their potential for sorption of crystal violet (CV) dye. Experiments were conducted to assess the effect of pH reaction time and CV loading on the adsorption process. The equilibrium adsorption capacity was higher with GBC700 (7.9 mg g−1) than GBC500 (4.9 mg g−1) and GBC300 (4.4 mg g−1), at pH 8. The CV sorption process was dependent on the pH, surface area and pore volume of biochar (GBC). Both Freundlich and Hill isotherm models fitted best to the equilibrium isotherm data suggesting cooperative interactions via physisorption and chemisorption mechanisms for CV sorption. The highest Hill sorption capacity of 125.5 mg g−1 was given by GBC700 at pH 8. Kinetic data followed the pseudo-second-order model, suggesting that the sorption process is more inclined toward the chemisorption mechanism. Pore diffusion, ππ electron donor–acceptor interaction and H-bonding were postulated to be involved in physisorption, whereas electrostatic interactions of protonated amine group of CV and negatively charged GBC surface led to a chemisorption type of adsorption. Overall, GBC produced as a by-product of the dendro industry could be a promising remedy for CV removal from an aqueous environment.

  • Concentrations, input prediction and probabilistic biological risk assessment of polycyclic aromatic hydrocarbons (PAHs) along Gujarat coastline 2017-08-11


    A comprehensive investigation was conducted in order to assess the levels of PAHs, their input prediction and potential risks to bacterial abundance and human health along Gujarat coastline. A total of 40 sediment samples were collected at quarterly intervals within a year from two contaminated sites—Alang-Sosiya Shipbreaking Yard (ASSBRY) and Navlakhi Port (NAV), situated at Gulf of Khambhat and Gulf of Kutch, respectively. The concentration of ΣPAHs ranged from 408.00 to 54240.45 ng g−1 dw, indicating heavy pollution of PAHs at both the contaminated sites. Furthermore, isomeric ratios and principal component analysis have revealed that inputs of PAHs at both contaminated sites were mixed-pyrogenic and petrogenic. Pearson co-relation test and regression analysis have disclosed Nap, Acel and Phe as major predictors for bacterial abundance at both contaminated sites. Significantly, cancer risk assessment of the PAHs has been exercised based on incremental lifetime cancer risks. Overall, index of cancer risk of PAHs for ASSBRY and NAV ranged from 4.11 × 10−6–2.11 × 10−5 and 9.08 × 10−6–4.50 × 10−3 indicating higher cancer risk at NAV compared to ASSBRY. The present findings provide baseline information that may help in developing advanced bioremediation and bioleaching strategies to minimize biological risk.

  • Error propagation in spatial modeling of public health data: a simulation approach using pediatric blood lead level data for Syracuse, New York 2017-08-08


    Lead poisoning produces serious health problems, which are worse when a victim is younger. The US government and society have tried to prevent lead poisoning, especially since the 1970s; however, lead exposure remains prevalent. Lead poisoning analyses frequently use georeferenced blood lead level data. Like other types of data, these spatial data may contain uncertainties, such as location and attribute measurement errors, which can propagate to analysis results. For this paper, simulation experiments are employed to investigate how selected uncertainties impact regression analyses of blood lead level data in Syracuse, New York. In these simulations, location error and attribute measurement error, as well as a combination of these two errors, are embedded into the original data, and then these data are aggregated into census block group and census tract polygons. These aggregated data are analyzed with regression techniques, and comparisons are reported between the regression coefficients and their standard errors for the error added simulation results and the original results. To account for spatial autocorrelation, the eigenvector spatial filtering method and spatial autoregressive specifications are utilized with linear and generalized linear models. Our findings confirm that location error has more of an impact on the differences than does attribute measurement error, and show that the combined error leads to the greatest deviations. Location error simulation results show that smaller administrative units experience more of a location error impact, and, interestingly, coefficients and standard errors deviate more from their true values for a variable with a low level of spatial autocorrelation. These results imply that uncertainty, especially location error, has a considerable impact on the reliability of spatial analysis results for public health data, and that the level of spatial autocorrelation in a variable also has an impact on modeling results.