Do earthworms impact metal mobility and availability in soil? - A review

The importance of earthworms to ecosystem functioning has led to many studies on the impacts of metals on earthworms. Far less attention has been paid to the impact that earthworms have on soil metals both in terms of metal mobility and availability. In this review we consider which earthworms have been used in such studies, which soil components have been investigated, which types of soil have been used and what measures of mobility and availability applied. We proceed to review proposed reasons for effects: changes in microbial populations, pH, dissolved organic carbon and metal speciation. The balance of evidence suggests that earthworms increase metal mobility and availability but more studies are required to determine the precise mechanism for this.     

Ultraviolet absorbance as a proxy for total dissolved mercury in streams

Stream water samples were collected over a range of hydrologic and seasonal conditions at three forested watersheds in the northeastern USA. Samples were analyzed for dissolved total mercury (THg_d), DOC concentration and DOC composition, and UV₂₅₄ absorbance across the three sites over different seasons and flow conditions. Pooling data from all sites, we found a strong positive correlation of THg_d to DOC (r² = 0.87), but progressively stronger correlations of THg_d with the hydrophobic acid fraction (HPOA) of DOC (r² = 0.91) and with UV₂₅₄ absorbance (r² = 0.92). The strength of the UV₂₅₄ absorbance-THg_d relationship suggests that optical properties associated with dissolved organic matter may be excellent proxies for THg_d concentration in these streams. Ease of sample collection and analysis, the potential application of in-situ optical sensors, and the possibility for intensive monitoring over the hydrograph make this an effective, inexpensive approach to estimate THg_d flux in drainage waters.     

Predicting bioremediation of hydrocarbons: Laboratory to field scale

There are strong drivers to increasingly adopt bioremediation as an effective technique for risk reduction of hydrocarbon impacted soils. Researchers often rely solely on chemical data to assess bioremediation efficiently, without making use of the numerous biological techniques for assessing microbial performance. Where used, laboratory experiments must be effectively extrapolated to the field scale. The aim of this research was to test laboratory derived data and move to the field scale. In this research, the remediation of over thirty hydrocarbon sites was studied in the laboratory using a range of analytical techniques. At elevated concentrations, the rate of degradation was best described by respiration and the total hydrocarbon concentration in soil. The number of bacterial degraders and heterotrophs as well as quantification of the bioavailable fraction allowed an estimation of how bioremediation would progress. The response of microbial biosensors proved a useful predictor of bioremediation in the absence of other microbial data. Field-scale trials on average took three times as long to reach the same endpoint as the laboratory trial. It is essential that practitioners justify the nature and frequency of sampling when managing remediation projects and estimations can be made using laboratory derived data. The value of bioremediation will be realised when those that practice the technology can offer transparent lines of evidence to explain their decisions.     

Ultrafine particles near a major roadway in Raleigh,North Carolina: Downwind attenuation and correlation with traffic-related pollutants

Ultrafine particles (UFPs, diameter < 100 nm) and co-emitted pollutants from traffic are a potential health threat to nearby populations. During summertime in Raleigh, North Carolina, UFPs were simultaneously measured upwind and downwind of a major roadway using a spatial matrix of five portable industrial hygiene samplers (measuring total counts of 20–1000 nm particles). While the upper sampling range of the portable samplers extends past the defined “ultrafine” upper limit (100 nm), the 20–1000 nm number counts had high correlation (Pearson R = 0.7–0.9) with UFPs (10–70 nm) measured by a co-located research-grade analyzer and thus appear to be driven by the ultrafine range. Highest UFP concentrations were observed during weekday morning work commutes, with levels at 20 m downwind from the road nearly fivefold higher than at an upwind station. A strong downwind spatial gradient was observed, linearly approximated over the first 100 m as an 8% drop in UFP counts per 10 m distance. This result agreed well with UFP spatial gradients estimated from past studies (ranging 5–12% drop per 10 m). Linear regression of other vehicle-related air pollutants measured in near real-time (10-min averages) against UFPs yielded moderate to high correlation with benzene (R² = 0.76), toluene (R² = 0.49), carbon monoxide (R² = 0.74), nitric oxide (R² = 0.80), and black carbon (R² = 0.65). Overall, these results support the notion that near-road levels of UFPs are heavily influenced by traffic emissions and correlate with other vehicle-produced pollutants, including certain air toxics.     

Examining intra-urban variation in fine particle mass constituents using GIS and constrained factor analysis

Recent studies have used land use regression (LUR) techniques to explain spatial variability in exposures to PM_2.5 and traffic-related pollutants. Factor analysis has been used to determine source contributions to measured concentrations. Few studies have combined these methods, however, to construct and explain latent source effects. In this study, we derive latent source factors using confirmatory factor analysis constrained to non-negative loadings, and develop LUR models to predict the influence of outdoor sources on latent source factors using GIS-based measures of traffic and other local sources, central site monitoring data, and meteorology. We collected 3–4 day samples of nitrogen dioxide (NO₂) and PM_2.5 outside of 44 homes in summer and winter, from 2003 to 2005 in and around Boston, Massachusetts. Reflectance analysis, X-ray fluorescence spectroscopy (XRF), and high-resolution inductively-coupled plasma mass spectrometry (ICP-MS) were performed on particle filters to estimate elemental carbon (EC), trace element, and water-soluble metals concentrations. Within our constrained factor analysis, a five-factor model was optimal, balancing statistical robustness and physical interpretability. This model produced loadings indicating long-range transport, brake wear/traffic exhaust, diesel exhaust, fuel oil combustion, and resuspended road dust. LUR models largely corroborated factor interpretations through covariate significance. For example, ‘long-range transport’ was predicted by central site PM_2.5 and season; ‘brake wear/traffic exhaust’ and ‘resuspended road dust’ by traffic and residential density; ‘diesel exhaust’ by percent diesel traffic on nearest major road; and ‘fuel oil combustion’ by population density. Results suggest that outdoor residential PM_2.5 source contributions can be partially predicted using GIS-based terms, and that LUR techniques can support factor interpretation for source apportionment. Together, LUR and factor analysis facilitate source identification, assessment of spatial and temporal variability, and more refined source exposure assignment for evaluation of source contributions to health outcomes in epidemiological studies.     

High time-resolved measurements of organic air toxics in different source regimes

High time-resolved (HTR) measurements can provide significant insight into sources and exposures of air pollution. In this study, an automated instrument was developed and deployed to measure hourly concentrations of 18 gas-phase organic air toxics and 6 volatile organic compounds (VOCs) at three sites in and around Pittsburgh, Pennsylvania. The sites represent different source regimes: a site with substantial mobile-source emissions; a residential site adjacent to a heavily industrialized zone; and an urban background site. Despite the close proximity of the sites (less than 13 km apart), the temporal characteristic of outdoor concentrations varied widely. Most of the compounds measured were characterized by short periods of elevated concentrations or plume events, but the duration, magnitude and composition of these events varied from site to site. The HTR data underscored the strong role of emissions from local sources on exposure to most air toxics. Plume events contributed more than 50% of the study average concentrations for all pollutants except chloroform, 1,2-dichloroethane, and carbon tetrachloride. Wind directional dependence of air toxic concentrations revealed that emissions from large industrial facilities affected concentrations at all of the sites. Diurnal patterns and weekend/weekday variations indicated the effects of the mixing layer, point source emissions patterns, and mobile source air toxics (MSATs) on concentrations. Concentrations of many air toxics were temporally correlated, especially MSATs, indicating that they are likely co-emitted. It was also shown that correlations of the HTR data were greater than lower time resolution data (24-h measurements). This difference was most pronounced for the chlorinated pollutants. The stronger correlations in HTR measurements underscore their value for source apportionment studies.     

Revised estimates of construction activity and emissions: Effects on ozone and elemental carbon concentrations in southern California

Emissions from diesel-powered construction equipment are an important source of nitrogen oxides (NO_x) and particulate matter (PM). A new emission inventory for construction equipment emissions is developed based on surveys of diesel fuel use; the revised inventory is compared to current emission inventories. California's OFFROAD model estimates are 4.5 and 3.1 times greater, for NO_x and PM respectively, than the fuel-based estimates developed here. The most relevant uncertainties are the overall amount of construction activity/diesel fuel use, exhaust emission factors for PM and NO_x, and the spatial allocation of emissions to county level and finer spatial scales. Construction permit data were used in this study to estimate spatial distributions of emissions; the resulting distribution is well correlated with population growth. An air quality model was used to assess the impacts of revised emission estimates. Increases of up to 15 ppb in predicted peak ozone concentrations were found in southern California. Elemental carbon and fine particle mass concentrations were in better agreement with observations using revised emission estimates, whereas negative bias in predictions of ambient NO_x concentrations increased.     

Effects of tree size and spatial distribution on growth of ponderosa pine forests under alternative management scenarios

Forest ecosystems may be actively managed toward heterogeneous stand structures to provide both economic (e.g., wood production and carbon credits) and environmental benefits (e.g., invasive pest resistance). In order to facilitate wider adoption of possibly more sustainable forest stand structures, defining growth expectations among alternative management scenarios is crucial. To estimate the effect of tree size and spatial distributions on growth for forest structures commonly considered in uneven-aged forest stand management, large (0.2 ha+) plots were established in 14 uneven-aged ponderosa pine stands in eastern Montana. All study trees were stem-mapped and measured for diameter and 10-year sapwood and basal area increment. A generalized growth model was developed to predict both total and merchantable 10-year basal area increment for nine hypothetical stand structures [three diameter distributions (reverse-J, irregular, flat) × three spatial distributions (clumpy, partial clumpy, uniform)]. Results indicate that the size and spatial distributions of individual trees have a considerable effect on overall stand growth. The greatest total stand growth was in stands with reverse “J” shaped tree size distributions, while the greatest merchantable stand growth was in stands with “flat” diameter distributions and uniform spatial distributions. Through better comprehension of generalized uneven-aged stand growth dynamics, forest managers may better assess the effects of alternative stand structures on stand growth while providing forest stand structures that may be more resilient in a changing climate.     

Accretion of heavy metals in the catfish <Emphasis Type="Italic">Bagrus bayad</Emphasis> from Taylor Creek,southern Nigeria

Heavy metals in the aquatic environment have, to date, come essentially from naturally occurring geochemical resources. However, this has been enhanced by anthropogenic activities such as crude oil exploration and exploitation activities, resulting in pollution in the Taylor Creek aquatic ecosystem. The catfish species Bagrus bayad and other environmental segments were collected from five selected sites along Taylor Creek, southern Nigeria, and total metal concentration determined. The concentration levels of the metals in B. bayad were higher than the values reported in the literature for fresh fish and may lead to a higher risk of harmful effects. The bivariate regression models relating metals in B. bayad and metals in the surface waters were significant (R ² ≥ 0.9002). The log (bio-concentration factor; BCF) values of Cr and Zn in B. bayad were the highest, whereas the lowest was found for Ni. The ecological distribution of the log (BCF) values was, for all the heavy metals, moderately stable over the creek. All log-transformed bio-magnification factors (BMF) in the creek were positive, which indicates that the metal concentration was greater in B. bayad than in suspended particulate matter (SPM). The absolute log (BMF) values of heavy metals can, therefore, be ranked in order of decreasing magnitude: Cr (3.26) > Zn (2.99) > Cd (2.93) > Fe (2.76) > Pb (2.66) > Mn (2.36) > Ni (2.24). This sequence indicates that toxic metals such as Cd, Cr and Pb are undergoing significant bio-reduction from SPM to B. bayad. The degree of correlation between the metals was different in B. bayad, which suggests that the sources of the metals polluting Taylor Creek were diverse.     

Population dynamics and the economics of invasive species management: the greenhouse whitefly in California-grown strawberries

In agriculture, relatively few efficacious control measures may be available for an invasive pest. In the case of a new insect pest, insecticide use decisions are affected by regulations associated with its registration, insect population dynamics, and seasonal market price cycles. We assess the costs and benefits of environmental regulations designed to regulate insecticide applications on an invasive species. We construct a bioeconomic model, based on detailed scientific data, of management decisions for a specific invasion: greenhouse whiteflies in California-grown strawberries. The empirical model integrates whitefly population dynamics, the effect of whitefly feeding on strawberry yields, and weekly strawberry price. We use the model to assess the optimality of alternative treatment programs on a simulated greenhouse whitefly population. Our results show that regulations may lead growers to "under-spray" when placed in an economic context, and provide some general lessons about the design of optimal invasive species control policies.