Geospatial Estimation of Mercury Contamination in Buffalo River Sediments

Forsythe, K. Wayne; Gawedzki, Adrian; Rodriguez, Peter S.; Irvine, Kimberly N.; Perrelli, Mary F.

doi:10.1080/15320383.2013.750266

Cited by 13 publications

(12 citation statements)

References 9 publications

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“…Because the highest pollutant concentrations are believed to be in low velocity, fine sediment zones, and not in high velocity, coarse sediment zones (Rhoads and Cahill, 1999), the conventional sampling protocols for pollution assessment of water bodies recommend sampling fine sediments on lentic geomorphic units of streams like pools or runs. In addition, hyporheic fluxes are generally ignored in sampling strategies of water or sediments (Boulton et al, 1998;Forsythe et al, 2013;Palumbo-Roe et al, 2012;Vervier et al, 1992).…”

Section: Introductionmentioning

confidence: 99%

Stream pollution concentration in riffle geomorphic units (Yzeron basin, France)

Namour

Schmitt

Eschbach

et al. 2015

Science of The Total Environment

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Section: Introductionmentioning

confidence: 99%

Stream pollution concentration in riffle geomorphic units (Yzeron basin, France)

Namour

Schmitt

Eschbach

et al. 2015

Science of The Total Environment

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“…Studies have indicated that kriging generally provides better results than spline and natural neighbour analysis (Voltz and Webster 1990;Laslett 1994;Pavão et al 2012;Duong and Gourbesville 2014). Different kriging approaches have been developed (Li and Heap 2014;Forsythe et al 2013; but ordinary kriging (OK) has been widely applied (Isaaks et al 1989;Robertson 2008;Soffianian et al 2015;Koko et al 2017) and was used here for the ponds and river. The general equation for estimating a value at a point z (Chang 2012) is:…”

Section: Spatial Analysis Of Heavy Metal Concentrations Using Gis Krimentioning

confidence: 99%

Spatial Patterns of Heavy Metals in the Sediments of a Municipal Wastewater Treatment Pond System and Receiving Waterbody, Cha am, Thailand

Andreas

Irvine

Jindal

et al. 2019

JWMM

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Cha am, a popular beach destination in Thailand, uses an aerated lagoon system with four ponds in series to treat its municipal wastewater. This study investigated the spatial pattern of heavy metal concentrations in the sediment deposited at the bottom of the four ponds and along the river receiving the treated wastewater discharge. Using a stratified random sampling scheme, between 11 and 14 surface grab samples were collected from each of the four ponds on two different dates in September and October 2016 (94 samples in total). An additional 17 samples were collected in December 2016 along the 1.8 km river section connecting the ponds to the ocean. A Bruker S1 Titan 600 X-ray fluorescence (XRF) analyser was used to determine metal concentrations in the air dried sediment samples. Ordinary kriging in ArcGIS10.1 indicated that while metal concentrations were greater in the middle areas of each pond, from pond to pond the metal concentrations exhibited different spatial trends. The ponds provide treatment for most of the metals analysed, with Student t-tests showing that mean concentrations of arsenic, chlorine and zinc decreased significantly from the first pond to the third pond but increased significantly in the fourth pond. Chromium concentration changed insignificantly between ponds; lead concentration decreased significantly from the first to the second pond, but there were insignificant changes in mean lead concentration thereafter. Concentrations of cadmium, cobalt, mercury and selenium were below the XRF limit of detection, but the mean levels of arsenic, chromium, copper, lead and manganese in each of the four ponds frequently exceeded Ontario Ministry of the Environment and Climate Change lowest effect level (LEL) guidelines for sediment. Metal levels in the upper reach of the river, closest to the pond discharge, were similar to the pond levels and generally decreased downstream. With the exception of zinc, metal levels detected in the river sediment frequently exceeded the LEL guidelines.

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“…Geographic information system (GIS) kriging is a spatial interpolation method to estimate a variable at an unmeasured location using observed values at nearby locations. Numerous studies have applied GIS kriging interpolation methods in the assessment of water and sediment quality to support management and remediation decision-making Murphy et al 2010;Lui et al 2011;Chen et al 2012b;Forsythe et al 2013). The primary objective of this study was to investigate the spatial variation of dissolved oxygen within the Cha-Am aeration lagoon system using the ordinary kriging (OK) interpolation method in ArcGIS10.1.…”

Section: Figure 1 Dissolved Oxygen Balance (Source: Sakalauskiene 2001)mentioning

confidence: 99%

Spatial and Temporal Variations of Dissolved Oxygen in Cha-Am Municipality Wastewater Treatment Ponds Using GIS Kriging Interpolation

Koko

Irvine²,

Jindal

et al. 2017

JWMM

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This study investigated the spatial and temporal variations in dissolved oxygen (DO) in the Cha-Am wastewater treatment ponds to assess treatment dynamics and to identify possible areas where the treatment train could be improved. Cha-Am is a small resort town with extensive beaches, located on the west coast of the Gulf of Thailand. The wastewater treatment system for Cha-Am consists of four ponds in sequence: aeration pond, sedimentation pond, extended aeration pond, and evaporation pond. Two YSI 6920 datasondes were installed near the inlet of the aeration pond and in the sedimentation pond, to measure dissolved oxygen (DO), pH, conductivity, temperature, and turbidity at 30 min time intervals over a 3 month period. DO averaged 3.09 mg/L and 3.33 mg/L, respectively in the aeration pond and in the sedimentation pond. DO generally varied over a diel cycle with higher values observed in midafternoon and lower values observed after midnight. DO often increased after a rainfall event. Ordinary Kriging (OK) interpolation in ArcGIS10.1 was used to map the spatial distribution of DO at different depths based on YSI spot measurements. OK indicated the highest DO concentrations were near the surface (0.5 m to 1.0 m); averaging 18.53 mg/L, 20.5 mg/L, 17.31 mg/L and 9.7 mg/L in the four ponds, but sometimes the concentrations were <2 mg/L near the bottom of the ponds. Two of the ponds are used as a wild catch fishery and low DO seems to negatively impact the fish. The spatial trend of DO shows that normally DO is lower at the inlet of the aeration pond than at its outlet even though mechanical aerators are operated through part of the day. Improved aeration and sunlight penetration through enhanced particle settling may be of benefit.

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Geospatial Estimation of Mercury Contamination in Buffalo River Sediments

Cited by 13 publications

References 9 publications

Stream pollution concentration in riffle geomorphic units (Yzeron basin, France)

Stream pollution concentration in riffle geomorphic units (Yzeron basin, France)

Spatial Patterns of Heavy Metals in the Sediments of a Municipal Wastewater Treatment Pond System and Receiving Waterbody, Cha am, Thailand

Spatial and Temporal Variations of Dissolved Oxygen in Cha-Am Municipality Wastewater Treatment Ponds Using GIS Kriging Interpolation

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