Phytoremediation is a method in which plants, soil microorganisms, amendments, and agronomic techniques interact to enhance contaminant degradation. We hypothesized that bermudagrass (Cynodon dactylon L) and an appropriate amount of N fertilizer would improve remediation of pyrene-contaminated Captina silt loam soil. The soil was contaminated with 0 or 1,000 mg pyrene/kg of soil and amended with urea at pyrene-C:urea-N (C:N) ratios of 4.5:1, 9:1, 18:1, or unamended (36:1). Either zero, one, two, or three bermudagrass sprigs were planted per pot and -33 kPa moisture potential was maintained. Pyrene concentrations, inorganic-N levels, shoot and root parameters, and pyrene degrader microbial numbers were measured following a 100-day greenhouse study. At a C:N ratio of 4.5:1, the presence of plants increased pyrene biodegradation from 31% for the no plant treatment to a mean of 62% for the one, two, and three plant treatments. With no plants and C:N ratios of 4.5:1, 9:1, 18:1, and 36:1, the mean pyrene biodegradation was 31, 52, 77, and 88%, respectively, indicating that increased inorganic-N concentration in the soil reduced pyrene degradation in the treatments without plants. Additionally, none of the one, two, or three plant treatments at any of the C:N ratios were different with a mean pyrene degradation value of 69% after 100 days. Pyrene resulted in reduced shoot and root biomass, root length, and root surface area, but increased root diameter. The pyrene degrading microbial numbers were approximately 10,000-fold higher in the pyrene-contaminated soil compared to the control. At the highest N rate, bermudagrass increased pyrene degradation compared to the no plant treatment, however, in the unvegetated treatment pyrene degradation was reduced with added N.

This study presents the analysis of two series of concentrations of airborne particulate matter (APM) collected in two exploratory campaigns aimed at elucidating the source-receptor problem (SRP) in the metropolitan area of Buenos Aires. Although several techniques have been previously applied to interpret these measurements, we have almost exclusively used here the method of angular distances among objects (ADO) to discuss its advantages as a tool in understanding environmental questions within the source-receptor framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed.

The presence of pharmaceuticals and personal care products (PPCPs) and endocrine disrupting chemicals (EDCs) in treated wastewater is gaining attention due to their potential environmental impact. An analytical method was developed to quantify estrogen compounds in samples from a concentrated wastewater matrix typical of water recycling systems used in space. The method employed conventional HPLC with UV detection. Solid phase extraction (SPE) was used to isolate the compounds of interest from wastewater. Spike-recovery tests in clean and wastewater matrices were used to test the extraction process. The results of these experiments suggest that deconjugation is the most predominant reaction occurring in the systems, as effluent concentrations of free estrogens typically exceeded influent concentrations. Despite the long retention times of the system or the near infinite solids retention time, free estrogens were not removed from graywater representative of space waste streams. For a closed-loop wastewater treatment system, these compounds may accumulate to levels requiring other removal mechanisms (i.e., reverse osmosis).

The enrichment factor, multivariate analysis and metal speciation studies were used to identify degree, source and dispersal of metal contamination in Khli Ti watershed, Thailand. Topsoil samples were collected throughout the watershed, analyzed for total metal concentration. Sequential extraction was also carried out to determine geochemical phases of metals which were identified as exchangeable and bound to carbonates, Fe–Mn oxides, organic matter and residuals. Soil characteristics including pH, total organic carbon, redox potential, cation exchange capacity and texture were also analyzed. Principal component analysis yielded three metal groups which explained 83% of the variance. The concentrations of metals which were derived from lithogenic origin, such as Co, Cr, Fe, Ni and V were in natural background levels and were mostly bound to the residual phase. The remaining elements (i.e. Ba, Cd, Cu, Pb, Sb and Zn) were associated with the contamination from previous activities of the Pb-ore concentrator and Zn–Pb mining. Anthropogenic contamination mainly increased Pb and Zn bound to Fe–Mn oxides at the expense of residual fraction. Even though low exchangeable Pb contents in Khli Ti soils indicated low availability to plants, Pb bound to Fe–Mn oxides fraction might increase its mobility under reducing conditions.

Aluminium is a non-essential element for biological systems and is used in water and wastewater processes that rely on (micro)biological purification processes. The effect of Al doses ranging from 100 to 2,000 μg/l on the microbial dissolved oxygen uptake (respiration) over a 24-h period was assessed. Results indicated that Al can reduce the 24-h respiration, but the effects of pH depression due to Al dosing during testing should be taken into account.

A wide variety of aquatic organisms, including juvenile salmonids, assess local predation risks using chemosensory cues. Such chemical cues are typically released from injured conspecifics and their detection may lead to species-typical antipredator behaviour, increasing the probability of prey to survive during predator encounters. Studies have demonstrated however, that under weak acidification (pH ~6.0), the response towards these chemical alarm cues is impaired. However, it remains unknown if the loss of response is graded (i.e., the behavioural response decreases with a reduction in pH) or if there is a threshold pH at which prey can no longer detect the alarm cues. We conducted two laboratory experiments to examine the effects of a graded reduction in pH on the behavioural response of juvenile rainbow trout to conspecific chemical alarm cues. The results of our first experiment suggest that at pH 6.6 and above, the alarm cues elicited a strong antipredator response, while alarm cues buffered to pH 6.2 did not (i.e. not different from distilled water). However, alarm cues buffered to pH 6.4 elicited a weak response, suggesting a graded response. We directly tested this in our second experiment using a repeated measures design. The response to alarm cues at varying pH levels did indeed follow a graded loss of function. Together, our results suggest that juvenile rainbow trout exhibit a reduction in the response to conspecific alarm cues proportional to ambient acidity and that the response to these critically important cues is lost at pH below 6.4. As the detection and response to these chemical alarm cues have been shown to confer direct survival benefit to individuals, these results are therefore presented in relation to possible sub-lethal effects of anthropogenic acidification to freshwater fish.

A comprehensive review of the single and sequential extraction schemes for metal fractionation in environmental samples such as soil and industrially contaminated soils, sewage sludge and sludge amended soils, road dust and run off, waste and miscellaneous materials along with other approaches of sequential extraction methods are being presented. A discussion on the application of chemometric methods in sequential extraction analysis is also being given. The study of single and sequential extraction methods for various reference materials are also being looked into. The review covers several aspects of the single and sequential extraction methodologies. The use of each reagents involved in these schemes are also discussed briefly. Finally the present upto date information by different workers in various fields of environmental geochemistry along with the possible future developments are also being outlined.

Regional botanical surveys supported by field experiments suggest that atmospheric nitrogen deposition threatens the balance between species and causes loss of biodiversity within plant communities. Methods are required to monitor the nitrogen status of vegetation at a landscape scale and therefore the potential for ecological change. Remote sensing has the potential to monitor a number of plant biophysical and chemical variables, but its application to monitor the nitrogen status of native vegetation remains limited and untested. Using field spectroscopy, canopy reflectance measurements were taken from two heathland field sites and heather (Calluna vulgaris) plants grown in a greenhouse. The nitrogen concentration was determined through destructive sampling and chemical analysis. Stepwise multiple regression analysis was used to identify the wavebands most associated with nitrogen concentration and despite high variation in the selected wavebands between the three datasets, most of these wavebands were associated with nitrogen and protein absorption features within the spectral region 1,990–2,170 nm. Results highlight the potential of remote sensing as a bio-monitoring technique to estimate foliar nitrogen status in native plants.

In this paper, downward movement and availability of copper in soils irrigated with CuSO₄ algaecide treated water were examined using column leaching experiments. Two simulations considering 1 and 10 years irrigation period were conducted at copper application rate of about 18.7 kg CuSO₄/ha/year. Effluent copper concentrations and vertical distribution of acid and DTPA-extractable copper in the soil columns were determined. Nearly 99% of the applied copper was retained in the soil with a C e/C ₀ values on the order of 10⁻³. Retention profiles showed that copper was retained in the upper 2 to 3 cm of the soil. However, a significant fraction of the retained copper was detected in available form (DTPA-Cu) suggesting that plants toxicity could be a major limitation for the use of CuSO₄ treatment in irrigation water.

Environmental regulations often rely on limits or thresholds to indicate an acceptable pollutant load. Estimates of the Risk of Exceeding such Thresholds (RET) are often based on a single model deemed to be the best for the particular pollutant or particular case. However, if many models make different predictions but explain the data almost equally well, predictions based on a single model may omit important information contained in other models that fit almost as well as the “best” single model. More accurate assessments of RET may result if multiple models are considered. We compared performance of the single best model relative to that of an ensemble of models estimated by bagging (Bootstrap AGGregatING) using the example of soil P concentrations and the risk of exceeding environmental limits of soil P concentrations in the watershed of Lake Mendota, Wisconsin, USA. Bagging yielded significantly better predictions of the risk of exceeding a threshold level of soil P (99.6% accuracy versus 74% for single-model prediction at a 20 mg kg⁻¹ threshold). Use of multiple model techniques can improve estimates of RET over a range of realistic thresholds in other management situations where thresholds are important including eutrophication, desertification, fisheries, and many types of pollution control.