Sediment quality in the Douro river estuary based on trace metal contents, macrobenthic community and elutriate sediment toxicity test (ESTT)

The aim of this study was to evaluate the sediment quality in the mesotidal Douro River estuarine environment, in order to identify areas where sediment contamination could cause ecosystem degradation. Samples were obtained in five locations and sediment characterised for grain size, total organic matter, total-recoverable metals (Al, Fe, Cu, Pb, Cr, Ni, Cd, Zn and Mn), as well as acid volatile sulfide (AVS) and simultaneously extracted metals (SEM). In situ effects were evaluated by examining the macrobenthic community structure. An elutriate sediment toxicity test (ESTT) was used to estimate the amount of metals and nutrients that could be exchanged with the water column through resuspension, and its positive or negative effects on the growth of the micro-alga Emiliania huxleyi in a 10 day test. Anthropogenic metal contamination was identified at the north bank of the Douro estuary, with deleterious effects on the macrobenthic community, namely decrease in number of species and diversity. This contamination could possibly also be toxic for water column organisms, in case of resuspension, as shown by the ESTT. Sediments from the salt marsh at the south bank showed an impoverished macrobenthic community and elutriate toxicity, which appeared to be due to anaerobic conditions. This study clearly shows the usefulness of the ESST approach to assess the biological effect of resuspension of estuarine sediments.     

Assessment of Metal Contamination in Doñana National Park (Spain) using Crayfish (Procamburus Clarkii)

Water quality assessment in the Aznalcollar area was attempted using multivariate methods based on heavy metal concentrations in red swamp crayfish (Procamburus clarkii). Trace levels of four heavy metals, copper (Cu), zinc (Zn), cadmium (Cd) and lead (Pb), were detected in crayfish from eleven different stations. Principal component analysis (PCA) highlighted a gradient of contamination between the sampling stations. Cluster analysis (CA) distinguished three groups of stations. Discriminant analysis also differentiated three groups. The group centroids of the first discriminant function were used to devise an index that varies according to the source of the crayfish. These standardized values are proposed for use as a water quality index. The ability of this index to successfully predict environmental quality was proved with random samples.     

Mean Vehicle Speed Distributions for the Spatiotemporal Estimation of Exhaust Emissions

Link Emissions Models estimate traffic-related air pollution emissions at the individual road link level and inform governmental policies for air quality management. The current South Australian Link Emissions Model (CLEM) assumes constant spatiotemporal traffic flow at a single fixed mean speed, a potential limitation as the variability of exhaust emissions with vehicle speed has been established in the literature.We extend CLEM to eliminate the assumption of constant traffic flow, through the derivation of mean Australian vehicle speed distributions for different road types. Specifically, we successfully model the vehicle speed profile data from the second National In-Service Emissions study using Nearest Neighbour Kernel Density Estimation. We propose a mean speed Distribution Link Emissions Model (DLEM) for exhaust emission estimation based on the derived mean speed distributions. DLEM is an augmented, enhanced version of CLEM, accommodating a range of vehicle speeds and road types. The performance of the extended model, DLEM, is analysed in comparison to the current model, CLEM, through a case study analysis of vehicle exhaust emissions on a typical arterial road in Adelaide, South Australia. Results indicate use of DLEM and, by extension, mean vehicle speed distributions, has a strong impact on emission estimation. In particular, the fixed speed model, CLEM, may be substantially underestimating exhaust emissions of carbon monoxide, non-methane volatile organic compounds and particulate matter less than 2.5 μm in diameter. These are common exhaust pollutants that have been extensively linked with adverse health effects including respiratory morbidity and premature mortality.