Structural changes in lake functioning induced from nutrient loading and climate variability

Climate variability is increasingly recognized as an important regulatory factor, capable of influencing the structural properties of aquatic ecosystems. Lakes appear to be particularly sensitive to the ecological impacts of climate variability, and several long time series have shown a close coupling between climate, lake thermal properties and individual organism physiology, population abundance, community structure, and food web dynamics. Thus, understanding the complex interplay among meteorological forcing, hydrological variability, and ecosystem functioning is essential for improving the credibility of model-based water resources/fisheries management. Our objective herein is to examine the relative importance of the ecological mechanisms underlying plankton seasonal variability in Lake Washington, Washington State (USA), over a 35-year period (1964–1998). Our analysis is founded upon an intermediate complexity plankton model that is used to reproduce the limiting nutrient (phosphate)–phytoplankton–zooplankton–detritus (particulate phosphorus) dynamics in the lake. Model parameterization is based on a Bayesian calibration scheme that offers insights into the degree of information the data contain about model inputs and allows obtaining predictions along with uncertainty bounds for modeled output variables. The model accurately reproduces the key seasonal planktonic patterns in Lake Washington and provides realistic estimates of predictive uncertainty for water quality variables of environmental management interest. A principal component analysis of the annual estimates of the underlying ecological processes highlighted the significant role of the phosphorus recycling stemming from the zooplankton excretion on the planktonic food web variability. We also identified a moderately significant signature of the local climatic conditions (air temperature) on phytoplankton growth (r = 0.41), herbivorous grazing (r = 0.38), and detritus mineralization (r = 0.39). Our study seeks linkages with the conceptual food web model proposed by Hampton et al. [Hampton, S.E., Scheuerell, M.D., Schindler, D.E., 2006b. Coalescence in the Lake Washington story: interaction strengths in a planktonic food web. Limnol. Oceanogr. 51, 2042–2051.] to emphasize the “bottom-up” control of the Lake Washington plankton phenology. The posterior predictive distributions of the plankton model are also used to assess the exceedance frequency and confidence of compliance with total phosphorus (15 μg L⁻¹) and chlorophyll a (4 μg L⁻¹) threshold levels during the summer-stratified period in Lake Washington. Finally, we conclude by underscoring the importance of explicitly acknowledging the uncertainty in ecological forecasts to the management of freshwater ecosystems under a changing global environment.     

A Bayesian hierarchical framework for calibrating aquatic biogeochemical models

Model practitioners increasingly place emphasis on rigorous quantitative error analysis in aquatic biogeochemical models and the existing initiatives range from the development of alternative metrics for goodness of fit, to data assimilation into operational models, to parameter estimation techniques. However, the treatment of error in many of these efforts is arguably selective and/or ad hoc. A Bayesian hierarchical framework enables the development of robust probabilistic analysis of error and uncertainty in model predictions by explicitly accommodating measurement error, parameter uncertainty, and model structure imperfection. This paper presents a Bayesian hierarchical formulation for simultaneously calibrating aquatic biogeochemical models at multiple systems (or sites of the same system) with differences in their trophic conditions, prior precisions of model parameters, available information, measurement error or inter-annual variability. Our statistical formulation also explicitly considers the uncertainty in model inputs (model parameters, initial conditions), the analytical/sampling error associated with the field data, and the discrepancy between model structure and the natural system dynamics (e.g., missing key ecological processes, erroneous formulations, misspecified forcing functions). The comparison between observations and posterior predictive monthly distributions indicates that the plankton models calibrated under the Bayesian hierarchical scheme provided accurate system representations for all the scenarios examined. Our results also suggest that the Bayesian hierarchical approach allows overcoming problems of insufficient local data by “borrowing strength” from well-studied sites and this feature will be highly relevant to conservation practices of regions with a high number of freshwater resources for which complete data could never be practically collected. Finally, we discuss the prospect of extending this framework to spatially explicit biogeochemical models (e.g., more effectively connect inshore with offshore areas) along with the benefits for environmental management, such as the optimization of the sampling design of monitoring programs and the alignment with the policy practice of adaptive management.     

Gas-phase and aerosol chemistry interactions in South Europe and the Mediterranean region

The atmospheric chemical composition is affected by the interaction mechanisms among gases and particulate matter through a wide range of chemical reactions that can occur with the aid of particulate matter (e.g. particles act as reacting or absorbing surfaces) or be influenced by the presence of particulate matter in the atmosphere (photochemical reactions). Physical and chemical processes are also bonded in an interactive way that often leads to the influence of the radiation budget, cloud physics and the warming or cooling of the lower atmospheric levels. The Euro-Mediterranean region is a key-sensitive area due to the unique climatic and air quality characteristics associated with the regional climatic patterns, geomorphology (land and water contrast) and coexistence of pollutants from different origin. Focusing on this region, the gas-aerosol interactions are studied using state-of-the-art atmospheric and chemical transport modeling tools following the necessary development in the chemical transport model CAMx. Sensitivity and large-scale simulations have shown significant responses of the modeling system to the inclusion of natural species emissions, the direct shading effect of dust particles on photochemical processes and the formation of new types of aerosols through heterogeneous uptake of gases on dust particles. Including such interactions in the chemical transport model often led to the improvement of the model performance compared with available measurements in the region.     

Environmental issues and management strategies for waste electronic and electrical equipment

Issues surrounding the impact and management of discarded or waste electronic and electrical equipment (WEEE) have received increasing attention in recent years. This attention stems from the growing quantity and diversity of electronic and electrical equipment (EEE) used by modern society, the increasingly rapid turnover of EEE with the accompanying burden on the waste stream, and the occurrence of toxic chemicals in many EEE components that can pose a risk to human and environmental health if improperly managed. In addition, public awareness of the WEEE or "e-waste" dilemma has grown in light of popular press features on events such as the transition to digital television and the exportation of WEEE from the United States and other developed countries to Africa, China, and India, where WEEE has often not been managed in a safe manner (e.g., processed with proper safety precautions, disposed of in a sanitary landfill, combusted with proper air quality procedures). This paper critically reviews current published information on the subject of WEEE. The definition, magnitude, and characteristics of this waste stream are summarized, including a detailed review of the chemicals of concern associated with different components and how this has changed and continues to evolve over time. Current and evolving management practices are described (e.g., reuse, recycling, incineration, landfilling). This review discusses the role of regulation and policies developed by governments, institutions, and product manufacturers and how these initiatives are shaping current and future management practices.     

Sustainable use of water in the Aegean Islands

Water demands in the Aegean Islands have increased steadily over the last decade as a result of a building boom for new homes, hotels, and resorts. The increase in water demand has resulted in the disruption of past sustainable water management practices. At present, most freshwater needs are met through the use of the limited groundwater, desalinated seawater, and freshwater importation. Wastewater reclamation, not used extensively, can serve as an alternative source of water, for a variety of applications now served with desalinated and imported water. Three alternative processes: desalination, importation, and water reclamation are compared with respect to cost, energy requirements and long-term sustainability. Based on the comparisons made, water reclamation and reuse should be components of any long-term water resources management strategy.     

Carbonation of wellbore cement by CO2 diffusion from caprock

To evaluate the risk of corrosion of cement by geosequestered CO₂, samples are being retrieved from wells placed in natural CO₂ deposits [e.g., Crow et al., 2009]. If the cement passing through the cap rock is carbonated, it may indicate that annular gaps or cracks have allowed carbonic acid to come into contact with the cement. However, it must be recognized that the pore water in the cap rock has become saturated with CO₂ over geological time. After the well is placed, the CO₂ will diffuse toward the cement and react with it. A simple analysis of the diffusion kinetics demonstrates that carbonation depths of millimeters to centimeters can be expected from this reaction within the lifetime of a well, in the absence of any cracks or gaps. Therefore, the occurrence of carbonation in cement sealing natural CO₂ deposits must be interpreted with caution.     

Surfactive stabilization of multi-walled carbon nanotube dispersions with dissolved humic substances

Soil humic substances (HS) stabilize carbon nanotube (CNT) dispersions, a mechanism we hypothesized arose from the surfactive nature of HS. Experiments dispersing multi-walled CNT in solutions of dissolved Aldrich humic acid (HA) or water-extractable Catlin soil HS demonstrated enhanced stability at 150 and 300 mg L⁻¹ added Aldrich HA and Catlin HS, respectively, corresponding with decreased CNT mean particle diameter (MPD) and polydispersivity (PD) of 250 nm and 0.3 for Aldrich HA and 450 nm and 0.35 for Catlin HS. Analogous trends in MPD and PD were observed with addition of the surfactants Brij 35, Triton X-405, and SDS, corresponding to surfactant sorption maximum. NEXAFS characterization showed that Aldrich HA contained highly surfactive domains while Catlin soil possessed a mostly carbohydrate-based structure. This work demonstrates that the chemical structure of humic materials in natural waters is directly linked to their surfactive ability to disperse CNT released into the environment.     

Vegetation exposure to ozone over the continental United States: Assessment of exposure indices by the Eta-CMAQ air quality forecast model

The main use of air quality forecast (AQF) models is to predict ozone (O₃) exceedances of the primary O₃ standard for informing the public of potential health concerns. This study presents the first evaluation of the performance of the Eta-CMAQ air quality forecast model to predict a variety of widely used seasonal mean and cumulative O₃ exposure indices associated with vegetation using the U.S. AIRNow O₃ observations. These exposure indices include two concentration-based O₃ indices, M7 and M12 (the seasonal means of daytime 7-h and 12-h O₃ concentrations, respectively), and three cumulative exposure-based indices, SUM06 (the sum of all hourly O₃ concentrations ≥ 0.06 ppm), W126 (hourly concentrations weighed by a sigmoidal weighting function), and AOT40 (O₃ concentrations accumulated over a threshold of 40 ppb during daylight hours). During a three-month simulation (July–September 2005), the model over predicted the M7 and M12 values by 8–9 ppb, or a NMB value of 19% and a NME value of 21%. The model predicts a central belt of high O₃ extending from Southern California to Middle Atlantic where the seasonal means, M7 and M12 (the seasonal means of daytime 7-h and 12-h O₃ concentrations), are higher than 50 ppbv. In contrast, the model is less capable of reproducing the observed cumulative indices. For AOT40, SUM06 and W126, the NMB and NME values are two- to three-fold of that for M7, M12 or peak 8-h O₃ concentrations. The AOT40 values range from 2 to 33 ppm h by the model and from 1 to 40 ppm h by the monitors. There is a significantly higher AOT40 value experienced in the United States in comparison to Europe. The domain-wide mean SUM06 value is 14.4 ppm h, which is about 30% higher than W126, and 40% higher than AOT40 calculated from the same 3-month hourly O₃ data. This suggests that SUM06 and W126 represent a more stringent standard than AOT40 if either the SUM06 or the W126 was used as a secondary O₃ standard. Although CMAQ considerably over predicts SUM06 and W126 values at the low end, the model under predicts the extreme high exposure values (>50 ppm h). Most of these extreme high values are found at inland California sites. Based on our analysis, further improvement of the model is needed to better capture cumulative exposure indices.     

Assimilating concentration observations for transport and dispersion modeling in a meandering wind field

Assimilating concentration data into an atmospheric transport and dispersion model can provide information to improve downwind concentration forecasts. The forecast model is typically a one-way coupled set of equations: the meteorological equations impact the concentration, but the concentration does not generally affect the meteorological field. Thus, indirect methods of using concentration data to influence the meteorological variables are required. The problem studied here involves a simple wind field forcing Gaussian dispersion. Two methods of assimilating concentration data to infer the wind direction are demonstrated. The first method is Lagrangian in nature and treats the puff as an entity using feature extraction coupled with nudging. The second method is an Eulerian field approach akin to traditional variational approaches, but minimizes the error by using a genetic algorithm (GA) to directly optimize the match between observations and predictions. Both methods show success at inferring the wind field. The GA-variational method, however, is more accurate but requires more computational time. Dynamic assimilation of a continuous release modeled by a Gaussian plume is also demonstrated using the genetic algorithm approach.