Fractionation of heavy metals in liquefied chromated copper arsenate 9-treated wood sludge using a modified BCR-sequential extraction procedure

Chromated copper arsenate (CCA)-treated wood was liquefied with polyethylene glycol/glycerin and sulfuric acid. After liquefaction, most CCA metals (98% As, 92% Cr, and 83% Cu) were removed from liquefied CCA-treated wood by precipitation with calcium hydroxide. The original CCA-treated wood and liquefied CCA-treated wood sludge were fractionated by a modified Community Bureau of Reference (BCR) sequential extraction procedure. The purpose of the BCR-sequential extraction used in this study was to examine the availability of CCA metals in treated wood for reuse. Both As and Cr had a slightly higher concentration in the sludge sample than in original CCA-treated wood. The sequential extraction showed that As and Cr were principally existed in an oxidizable fraction (As, 67%; Cr, 88%) in original CCA-treated wood. Only 1% of both As and Cr were extracted by hot nitric acid with the last extraction step. The distribution of As and Cr changed markedly in liquefied CCA-treated wood sludge.The amount of As in the exchangeable/acid extractable fraction increased from 16% to 85% while the amount of Cr increased from 3% to 54%. Only about 3% of As was present in the oxidizable fraction. However, there was still about 34% of Cr in the same fraction. Based on these results from sequential extraction procedures, it can be concluded that the accessibilities of CCA metals increase markedly by the liquefaction–precipitation process.     

A spatially explicit framework for quantifying downstream hydrologic conditions

Continued improvements in spatial datasets and hydrological modeling algorithms within Geographic Information Systems (GISs) have enhanced opportunities for watershed analysis. With more detailed hydrology layers and watershed delineation techniques, we can now better represent and model landscape to water quality relationships. Two challenges in modeling these relationships are selecting the appropriate spatial scale of watersheds for the receiving stream segment, and handling the network or pass-through issues of connected watersheds. This paper addresses these two important issues for enhancing cumulative watershed capabilities in GIS. Our modeling framework focuses on the delineation of stream-segment-level watershed boundaries for 1:24 000 scale hydrology, in combination with a topological network model. The result is a spatially explicit, vector-based, spatially cumulative watershed modeling framework for quantifying watershed conditions to aid in restoration. We demonstrate the new insights available from this modeling framework in a cumulative mining index for the management of aquatic resources in a West Virginia watershed.     

Evaluating landfill disposal of chromated copper arsenate (CCA) treated wood and potential effects on groundwater: evidence from Florida

Chromated copper arsenate (CCA) treated wood has been used for more than 50 years. Recent attention has been focused on appropriate disposal of CCA-treated wood when its service life ends. Groups in the US and Europe concerned with the possibility of arsenic migration to groundwater from disposed CCA-treated wood have proposed that consumers be required to dispose of the wood as a hazardous waste, in the most protective of landfills. We examined available data for evidence of arsenic migration from unlined construction and demolition (C&D) debris landfills in Florida, where CCA-treated wood is disposed. Florida was chosen because soil, groundwater, landfill design, weather, and levels of CCA-treated wood use make the state a uniquely sensitive indicator for observing arsenic migration from CCA-treated wood disposal sites, should it occur. We developed and quality-checked a CCA-treated wood disposal model to estimate the amount of wood and associated arsenic disposed. By 2000, an estimated 13 million kg of arsenic in CCA-treated wood was disposed in Florida; however, groundwater monitoring data do not indicate that arsenic is migrating from unlined C&D landfills. Our results provide evidence that highly stringent regulation of CCA-treated wood disposal, such as treatment as a hazardous waste, is unnecessary.     

Combined monitoring and modeling indicate the most effective agricultural best management practices

Although water quality problems associated with agricultural nonpoint source (NPS) pollution have prompted the rapid and widespread adoption of a variety of so called "best management practices" (BMPs), there have been few realistic efforts to assess their combined effectiveness in reducing NPS pollution. This study used the Variable Source Loading Function (VSLF) model, a distributed watershed model, to simulate phosphorus (P) loading from an upstate New York dairy farm before and after the implementation of a suite of BMPs. With minimal calibration, the model calculates the dissolved P (DP) losses from impervious surfaces (e.g., barnyards), the plant/soil complex, field-applied manure, and loads associated with baseflow conditions. The simulated DP loads agreed well with measured loads for both the pre-BMP and post-BMP periods. More importantly, results showed that BMPs reduced DP loads by 35%, which is over half of the expected reduction if all manure was removed from the watershed, i.e., approximately 50% reduction. The model results indicate that had no BMPs been installed DP loads would be approximately 37% greater than observed at the watershed outlet. The most effective BMPs were those that disassociated pollutant loading areas from areas prone to generating runoff, i.e., hydrologically sensitive areas. By contrast, attempts to reduce P content in manure were somewhat less effective. This study demonstrates that a combination of distributed, mechanistic modeling and long-term monitoring provides better insights into the effectiveness of water quality protection efforts than either individually.     

Assessment of chlorophyll-a as a criterion for establishing nutrient standards in the streams and rivers of Illinois

Nutrient enrichment is a frequently cited cause for biotic impairment of streams and rivers in the USA. Efforts are underway to develop nutrient standards in many states, but defensible nutrient standards require an empirical relationship between nitrogen (N) or phosphorus (P) concentrations and some criterion that relates nutrient levels to the attainment of designated uses. Algal biomass, measured as chlorophyll-a (chl-a), is a commonly proposed criterion, yet nutrient-chl-a relationships have not been well documented in Illinois at a state-wide scale. We used state-wide surveys of >100 stream and river sites to assess the applicability of chl-a as a criterion for establishing nutrient standards for Illinois. Among all sites, the median total P and total N concentrations were 0.185 and 5.6 mg L(-1), respectively, during high-discharge conditions. During low-discharge conditions, median total P concentration was 0.168 mg L(-1), with 25% of sites having a total P of > or =0.326 mg L(-1). Across the state, 90% of the sites had sestonic chl-a values of < or =35 microg L(-1), and watershed area was the best predictor of sestonic chl-a. During low discharge there was a significant correlation between sestonic chl-a and total P for those sites that had canopy cover < or =25% and total P of < or =0.2 mg L(-1). Results suggest sestonic chl-a may be an appropriate criterion for the larger rivers in Illinois but is inappropriate for small rivers and streams. Coarse substrate to support benthic chl-a occurred in <50% of the sites we examined; a study using artificial substrates did not reveal a relationship between chl-a accrual and N or P concentrations. For many streams and rivers in Illinois, nutrients may not be the limiting factor for algal biomass due to the generally high nutrient concentrations and the effects of other factors, such as substrate conditions and turbidity.     

The latent structure of landscape perception: A mean and covariance structure modeling approach

Mean and covariance structure (MACS) modeling is used to explore a central question in contemporary environmental psychology: “How should human environments be conceptualized?”. Specifically, an expanded version of the preference model of landscape perception proposed by S. and R. Kaplan is presented. The proposed model not only constitutes a respecification and deepening of the Kaplans’ model but also presents an integrative perspective that simultaneously considers the interrelations among cognitive, motivational, affective, evaluative, and behavioral tendencies in landscape perception. In a series of four studies, we develop and validate multi-item measures of various constructs, test the measure invariances, and the structural model. The findings reveal the crucial role of various constructs that originally were hypothesized by the Kaplans but never included in the model tests. In addition, positive and negative feelings induced by the landscape emerge as antecedents to landscape perception. The implications of these findings are discussed.