Correction to: Documenting lemming population change in the Arctic: Can we detect trends?

Ambio - In the original published article, some of the symbols in figure 1A were modified incorrectly during the typesetting and publication process. The correct version of the figure is provided...     

Marginal Abatement Costs and Marginal Welfare Costs for Greenhouse Gas Emissions Reductions: Results from the EPPA Model

Marginal abatement cost (MAC) curves, relationships between tonnes of emissions abated and the CO₂ (or greenhouse gas (GHG)) price, have been widely used as pedagogic devices to illustrate simple economic concepts such as the benefits of emissions trading. They have also been used to produce reduced-form models to examine situations where solving the more complex model underlying the MAC is difficult. Some important issues arise in such applications: (1) Are MAC relationships independent of what happens in other regions?, (2) are MACs stable through time regardless of what policies have been implemented in the past?, and (3) can one approximate welfare costs from MACs? This paper explores the basic characteristics of MAC and marginal welfare cost (MWC) curves, deriving them using the MIT Emissions Prediction and Policy Analysis model. We find that, depending on the method used to construct them, MACs are affected by policies abroad. They are also dependent on policies in place in the past and depend on whether they are CO₂-only or include all GHGs. Further, we find that MACs are, in general, not closely related to MWCs and therefore should not be used to derive estimates of welfare change. We also show that, as commonly constructed, MACs may be unreliable in replicating results of the parent model when used to simulate GHG policies. This is especially true if the policy simulations differ from the conditions under which the MACs were simulated.     

Changes in Near-Surface Temperature and Sea Level for the Post-SRES CO2-Stabilization Scenarios

Changes in global near-surface temperature and sea level are calculated from 2000 to 2100 for the Post-SRES (Special Report on Emissions Scenarios) scenarios that stabilize the CO₂ concentration early in the 22nd century. Seven stabilization scenarios are examined together with their corresponding SRES marker scenarios – A1, A1/S450, A1/S550, A1/S650, A2, A2/S550, A2/S750, B1, B1/S450, B2, and B2/S550 – where the number following the S indicates the stabilized CO₂ concentration in parts per million by volume (ppmv). The calculations are performed using an energy-balance-climate/upwelling-diffusion-ocean model for three values of the climate sensitivity, ΔT _2x =1.5, 2.5 and 4.5°C. The resulting reductions in global warming and sea-level rise for the stabilization scenarios relative to their corresponding marker scenario increases with ΔT _2x and are greater the lower the stabilized CO₂ concentration. For the S550 stabilization scenarios, the reductions in global warming and sea-level rise in 2100 range from 0.29°C and 3.31 cm for B2/S550 with ΔT _2x =1.5°C, to 1.23°C and 11.81 cm for A2/S550 with ΔT _2x =4.5°C. The percent reductions for the global warming and sea-level rise for each stabilization scenario are almost independent of ΔT _2x and range respectively from about 16% and 12% for the A1/S650 scenario to about 39% and 30% for the A1/S450 scenario. The geographical distributions of near-surface temperature change are constructed using a method to superpose the patterns simulated by our atmospheric general-circulation/mixed-layer-ocean model, individually for doubled CO₂ concentration and decupled SO₄ burden. Results are illustrated for the B2 and B2/S550 scenarios for ΔT _2x =2.5°C. The near-surface temperature changes of the B2/S550 scenario in 2100 are everywhere smaller than those for the B2 scenario, with values ranging from about 0.3°C in the tropics to 0.5°C over Antarctica and 0.7°C in the Arctic. The global results of this study are available on the web at: http://crga.atmos.uiuc.edu/research/post-sres.html. We would be pleased to collaborate with other researchers in using these results in impact and integrated-assessment studies. This revised version was published online in July 2006 with corrections to the Cover Date.     

Influence of home characteristics on airborne and dustborne endotoxin and β-D-glucan

The aim of this study was to assess the associations between airborne and dustborne microbial contaminants (endotoxin and β-D-glucan) and estimate the effects of home characteristics on exposure levels of these microbial contaminants. Endotoxin and β-D-glucan concentrations in airborne inhalable particles, airborne PM1 (<1 μm) and vacuumed dust from 184 residential homes were determined using specific Limulus amebocyte assays. Home characteristics were recorded by visual inspection and questionnaires. Linear regression and correlation analyses were performed. Inhalable endotoxin correlated with dust endotoxin (r = 0.34, p < 0.001) and PM1 endotoxin (r = 0.33, p < 0.001). Inhalable β-D-glucan correlated with dust β-D-glucan (r = 0.18, p < 0.01), but not with PM1 β-D-glucan. Significant correlation was also found between PM1 and dust concentrations for endotoxin (r = 0.26, p < 0.001), but not for β-D-glucan. Multivariate regression analyses showed only one significant association between airborne contaminants and environmental characteristics: inhalable β-D-glucan was positively associated with relative humidity with an effect size (change in the dependent variable corresponding to a unit increase in the independent variable) of 2.32 and p < 0.05. In contrast, several associations were found between dust concentrations and environmental characteristics. Dust endotoxin was positively associated with temperature (2.87, p < 0.01) and number of inhabitants (2.76, p < 0.01), whereas dust β-D-glucan was inversely associated with the presence of dogs (-2.24, p < 0.05) and carpet (-3.05, p < 0.01) in the home. In conclusion, dustborne contaminants were more strongly affected by home characteristics than airborne contaminants. Furthermore, even though statistically significant, the correlations between airborne and dustborne contaminants were weak. This indicates that airborne concentrations cannot be reliably predicted based on dustborne concentrations.     

Intelligent Databases Assist Transparent and Sound Economic Valuation of Ecosystem Services

Assessment and economic valuation of services provided by ecosystems to humans has become a crucial phase in environmental management and policy-making. As primary valuation studies are out of the reach of many institutions, secondary valuation or benefit transfer, where the results of previous studies are transferred to the geographical, environmental, social, and economic context of interest, is becoming increasingly common. This has brought to light the importance of environmental valuation databases, which provide reliable valuation data to inform secondary valuation with enough detail to enable the transfer of values across contexts. This paper describes the role of next-generation, intelligent databases (IDBs) in assisting the activity of valuation. Such databases employ artificial intelligence to inform the transfer of values across contexts, enforcing comparability of values and allowing users to generate custom valuation portfolios that synthesize previous studies and provide aggregated value estimates to use as a base for secondary valuation. After a general introduction, we introduce the Ecosystem Services Database, the first IDB for environmental valuation to be made available to the public, describe its functionalities and the lessons learned from its usage, and outline the remaining needs and expected future developments in the field.     

Biodegradation of Poly-ε-caprolactones and Poly-<Emphasis Type="SmallCaps">l</Emphasis>-lactides by Fungi

This work assessed biodegradation, by Aspergillus, Fusarium, Penicillium and Parengyodontium fungi, of four samples of poly-ε-caprolactone (PCL), three samples of poly-l-lactide (PLA) and one sample of poly-d,l-lactide (DL-PLA) produced by ring-opening polymerization initiated by aluminium complexes of corresponding lactones. Mesophilic fungal strains actively biodegrading PCL (F. solani) and PLA (Parengyodontium album and A. calidoustus) were selected. The rate of degradation by the selected fungi was found to depend on the physicochemical and mechanical properties of the polymers (molecular weight, polydispersity, crystallinity). The most degradable poly-ε-caprolactone sample was shown to have the lowest molecular weight; the most biodegradable polylactide DL-PLA had the lowest crystallinity. Mass spectral analysis of biodegraded polymer residues showed PCL to be degraded more intensively than PLA. It is established that in the case of Parengyodontium album the colonization of the films of polypropylene composites with DL-PLA is observed, which will undoubtedly contribute to their further destruction under the influence of abiotic factors in the environment.