Increased bioavailability of metals in two contrasting agricultural soils treated with waste wood-derived biochar and ash

Recycled waste wood is being increasingly used for energy production; however, organic and metal contaminants in by-products produced from the combustion/pyrolysis residue may pose a significant environmental risk if they are disposed of to land. Here we conducted a study to evaluate if highly polluted biochar (from pyrolysis) and ash (from incineration) derived from Cu-based preservative-treated wood led to different metal (e.g., Cu, As, Ni, Cd, Pb, and Zn) bioavailability and accumulation in sunflower (Helianthus annuus L.). In a pot experiment, biochar at a common rate of 2 % w/w, corresponding to ～50 t ha^?1, and an equivalent pre-combustion dose of wood ash (0.2 % w/w) were added to a Eutric Cambisol (pH 6.02) and a Haplic Podzol (pH 4.95), respectively. Both amendments initially raised soil pH, although this effect was relatively short-term, with pH returning close to the unamended control within about 7 weeks. The addition of both amendments resulted in an exceedance of soil Cu statutory limit, together with a significant increase of Cu and plant nutrient (e.g., K) bioavailability. The metal-sorbing capacity of the biochar, and the temporary increase in soil pH caused by adding the ash and biochar were insufficient to offset the amount of free metal released into solution. Sunflower plants were negatively affected by the addition of metal-treated wood-derived biochar and led to elevated concentration of metals in plant tissue, and reduced above- and below-ground biomass, while sunflower did not grow at all in the Haplic Podzol. Biochar and ash derived from wood treated with Cu-based preservatives can lead to extremely high Cu concentrations in soil and negatively affect plant growth. Identifying sources of contaminated wood in waste stream feedstocks is crucial before large-scale application of biochar or wood ash to soil is considered.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Source attribution and quantification of benzene event emissions in a Houston ship channel community based on real-time mobile monitoring of ambient air

A mobile laboratory equipped with a proton transfer reaction mass spectrometer (PTR-MS) operated in Galena Park, Texas, near the Houston Ship Channel during the Benzene and other Toxics Exposure Study (BEE-TEX). The mobile laboratory measured transient peaks of benzene of up to 37 ppb_v in the afternoon and evening of February 19, 2015. Plume reconstruction and source attribution were performed using the four-dimensional (4D) variational data assimilation technique and a three-dimensional (3D) micro-scale forward and adjoint air quality model based on mobile PTR-MS data and nearby stationary wind measurements at the Galena Park Continuous Air Monitoring Station (CAMS). The results of inverse modeling indicate that significant pipeline emissions of benzene may at least partly explain the ambient concentration peaks observed in Galena Park during BEE-TEX. Total pipeline emissions of benzene inferred within the 16-km² model domain exceeded point source emissions by roughly a factor of 2 during the observational episode. Besides pipeline leaks, the model also inferred significant benzene emissions from marine, railcar, and tank truck loading/unloading facilities, consistent with the presence of a tanker and barges in the Kinder Morgan port terminal during the afternoon and evening of February 19. Total domain emissions of benzene exceeded corresponding 2011 National Emissions Inventory (NEI) estimates by a factor of 2–6.

Implications:?Port operations involving petrochemicals may significantly increase emissions of air toxics from the transfer and storage of materials. Pipeline leaks, in particular, can lead to sporadic emissions greater than in emission inventories, resulting in higher ambient concentrations than are sampled by the existing monitoring network. The use of updated methods for ambient monitoring and source attribution in real time should be encouraged as an alternative to expanding the conventional monitoring network.     

Application of activated M/ZnO (M = Mn,Co, Ni,Cu, Ag) in photocatalytic degradation of diazo textile coloring dye

Activated ZnO powder has been prepared by procedures involving first its dissolution in nitric acid, then simultaneous treatment by adding NH₄OH and CO₂ bubbling leading to precipitation as Zn(OH)CO₃ (ZH) and further thermal decomposition of ZH at 400 °C. The gas evolution leads to formation of pores and increase in the specific surface area. Chemically activated M/ZnO powders doped with Mn, Co, Ni, Cu, and Ag have been obtained by the impregnation method. The samples have been characterized by ultraviolet-visible (UV-Vis) spectroscopy, diffuse reflectance (DR) UV-Vis, X-ray diffraction (XRD), single point Brunauer–Emmet–Teller (BET), scanning electron microscope (SEM), and X-ray photoelectron spectroscopy (XPS) methods. The experiments have shown that metal-doped activated ZnO powders possess higher photocatalytic activities in oxidative discoloration of model contaminant textile coloring dye Reactive Black 5 in slurry reactor compared to that of the pure ZnO. The XRD and XPS data have shown the presence of defects, nonstoichiometricity implying the formation of solid solutions. Copper-doped (1.5 wt%) activated ZnO (Cu²⁺ replaces Zn²⁺) is outstanding in its photocatalytic performance in discoloration of the dye due to the higher specific surface area and improved charge carrier separation.