Societal implications of sustainable energy action plans: from energy modelling to stakeholder learning

This article investigates the potential impact of sustainable energy action plans (SEAPs) on local development through a two-step methodology involving participatory planning and quantitative analysis. The first phase relies on a participatory system mapping (PSM) approach and generates a causal structure at the basis of the urban model. In the second phase, we transform the qualitative map into a system dynamic model which evaluates the effect of the SEAP on social, economic and environmental indicators. This methodology was applied to the case of Cascina Municipality (Italy). Through scenario analysis, we show that some indirect feedback can harm the achievement of the 20% emission reduction target. This process allows the local authority and stakeholders to evaluate the impact of emission reduction policies on CO₂ emissions and local development, thereby generating collective learning on the systemic implications of the plan. We show that this method can enhance the ambition of emission mitigation efforts by small towns.     

Seaweeds as bioindicators of heavy metals off a hot spot area on the Egyptian Mediterranean Coast during 2008–2010

Concentrations of Cu, Zn, Cd, Pb, Ni, Co, Fe, Mn, and Hg were measured successively in water, sediments, and six macroalgal species belonging to three algal classes during 3 years (2008–2010) from Abu Qir Bay, Alexandria, Egypt: Chlorophyceae (Enteromorpha compressa, Ulva fasciata), Phaeophyceae (Padina boryana), and Rhodophyceae (Jania rubens, Hypnea musciformis, Pterocladia capillacea). The study aimed to assess the bioaccumulation potential of the seaweeds, as well as to evaluate the extent of heavy metal contamination in the selected study site. Metals were analyzed using atomic absorption spectrophotometry coupled with MH-10 hydride system. The obtained data showed that the highest mean concentrations of Cu, Zn, Fe, and Mn were recorded in E. compressa; Cd, Ni, and Hg exhibited their highest mean concentrations in P. boryana, while Pb and Co were found in J. rubens. Abundance of the heavy metals in the algal species was as follow: Fe?>?Mn?>?Zn?>?Pb?>?Ni?>?Co?>?Cu?>?Cd?>?Hg. E. compressa showed the maximum metal pollution index (MPI) which was 11.55. Bioconcentration factor (BCF) for the metals in algae was relatively high with a maximum value for Mn. The Tomlinson pollution load index (PLI) values for the recorded algal species were low, which ranged between 1.00 in P. boryana and 2.72 in E. compressa. Enrichment factors for sediments were low fluctuating between 0.43 for Hg to 2.33 for Mn. Accordingly, the green alga E. compressa, brown alga P. boryana, and red alga J. rubens can be nominated as bioindicators. Based on MPI and PLI indices, Abu Qir Bay in the present study is considered as low-contaminated area.     

Combined Municipal Solid Waste and biomass system optimization for district energy applications

Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers. Finally, the sensitivity analysis is enhanced by a stochastic analysis to determine the effect of the volatility of parameters on the robustness of the model and the solution obtained.     

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.     

Rainwater toxicity and contamination study from São Paulo Metropolitan Region, Brazil

Wet deposition is an important process that removes pollutants from the atmosphere and transfers them to waters and soil. The goal of this study was to assess the biological effects of the atmospheric contamination of rainwater in the metropolitan area of São Paulo (MASP) using Daphnia similis, Ceriodaphnia dubia, and Vibrio fischeri. Experimental assays were carried out according to standard toxicity methodology. Twenty-three rainwater samples were collected from October 2007 to December 2008, at the Nuclear Research Institute (IPEN), in MASP. Major ions were determined by ionic chromatography, which showed NH₄ ⁺ and NO₃ ^? as prevalent ions. Ecotoxicological results confirmed toxic potential of rainwater, as all samples were toxic to D. similis and C. dubia. The V. fischeri luminescence reduction confirmed those negative effects of rainwater and percentage inhibition of relative luminescence ranged from 0.2 to 0.9 for 16 samples. Worse conditions were observed during the rainy season, suggesting convective rains are more effective in transferring contaminants and toxicity from atmosphere to surface.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

The city as a refuge for insect pollinators

Research on urban insect pollinators is changing views on the biological value and ecological importance of cities. The abundance and diversity of native bee species in urban landscapes that are absent in nearby rural lands evidence the biological value and ecological importance of cities and have implications for biodiversity conservation. Lagging behind this revised image of the city are urban conservation programs that historically have invested in education and outreach rather than programs designed to achieve high‐priority species conservation results. We synthesized research on urban bee species diversity and abundance to determine how urban conservation could be repositioned to better align with new views on the ecological importance of urban landscapes. Due to insect pollinators’ relatively small functional requirements—habitat range, life cycle, and nesting behavior—relative to larger mammals, we argue that pollinators put high‐priority and high‐impact urban conservation within reach. In a rapidly urbanizing world, transforming how environmental managers view the city can improve citizen engagement and contribute to the development of more sustainable urbanization.     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.