A synthesis of current knowledge on forests and carbon storage in the United States

Using forests to mitigate climate change has gained much interest in science and policy discussions. We examine the evidence for carbon benefits, environmental and monetary costs, risks and trade-offs for a variety of activities in three general strategies: (1) land use change to increase forest area (afforestation) and avoid deforestation; (2) carbon management in existing forests; and (3) the use of wood as biomass energy, in place of other building materials, or in wood products for carbon storage. We found that many strategies can increase forest sector carbon mitigation above the current 162-256 Tg C/yr, and that many strategies have co-benefits such as biodiversity, water, and economic opportunities. Each strategy also has trade-offs, risks, and uncertainties including possible leakage, permanence, disturbances, and climate change effects. Because approximately 60% of the carbon lost through deforestation and harvesting from 1700 to 1935 has not yet been recovered and because some strategies store carbon in forest products or use biomass energy, the biological potential for forest sector carbon mitigation is large. Several studies suggest that using these strategies could offset as much as 10-20% of current U.S. fossil fuel emissions. To obtain such large offsets in the United States would require a combination of afforesting up to one-third of cropland or pastureland, using the equivalent of about one-half of the gross annual forest growth for biomass energy, or implementing more intensive management to increase forest growth on one-third of forestland. Such large offsets would require substantial trade-offs, such as lower agricultural production and non-carbon ecosystem services from forests. The effectiveness of activities could be diluted by negative leakage effects and increasing disturbance regimes. Because forest carbon loss contributes to increasing climate risk and because climate change may impede regeneration following disturbance, avoiding deforestation and promoting regeneration after disturbance should receive high priority as policy considerations. Policies to encourage programs or projects that influence forest carbon sequestration and offset fossil fuel emissions should also consider major items such as leakage, the cyclical nature of forest growth and regrowth, and the extensive demand for and movement of forest products globally, and other greenhouse gas effects, such as methane and nitrous oxide emissions, and recognize other environmental benefits of forests, such as biodiversity, nutrient management, and watershed protection. Activities that contribute to helping forests adapt to the effects of climate change, and which also complement forest carbon storage strategies, would be prudent.     

Mercury removal, methylmercury formation, and sulfate-reducing bacteria profiles in wetland mesocosms

A pilot-scale model was constructed to determine if a wetland treatment system (WTS) could effectively remove low-level mercury from an outfall located at the Department of Energy's Savannah River Site. Site-specific hydrosoil was planted with giant bulrush, Scirpus californicus, and surface amended with gypsum (CaSO4) prior to investigating the biogeochemical dynamics of sediment-based sulfur and mercury speciation. On average, the pilot WTS decreased total mercury concentrations in the outfall stream by 50%. Transformation of mercury to a more "bioavailable" species, methylmercury, was also observed in the wetland treatment system. Methylmercury formation in the wetland was ascertained with respect to sediment biogeochemistry and S. californicus influences. Differences in sulfate-reduction rates (SRRs) were observed between mesocosms that received additional decomposing Scirpus matter and mesocosms that were permitted growth of the submerged macrophyte, Potamogeton pusillus. Relative abundance measurements of sulfate-reducing bacteria (SRB) as characterized using oligonucleotide probes were also noticeably different between the two mesocosms. A positive correlation between increased sulfide, dissolved total mercury, and dissolved methylmercury concentrations was also observed in porewater. The data suggest that soluble mercury-sulfide complexes were formed and contributed, in part, to a slight increase in mercury solubility. Observed increases in methylmercury concentration also suggest that soluble mercury-sulfide complexes represent a significant source of mercury that is "available" for methylation. Finally, a volunteer macrophyte, Potamogeton pusillus, is implicated as having contributed additional suspended particulate matter in surface water that subsequently reduced the pool of dissolved mercury while also providing an environment suitable for demethylation.     

Evaluation of the Ceilcote ionizing wet scrubber

The Ceilcote ionizing wet scrubber installed on a refractory brick kiln was evaluated with tests involving particulate mass emission, particle size distribution, and opacity. The overall efficiency was 93% with an average outlet opacity of 8% on a 1.68 m (5.5 ft) path length. The average particle cut diameter of the scrubber is 0.5 microns with a theoretical power input of 67 W/am³ (2.5 hp/1000 acfm). The theoretical power requirement for the ionizing wet scrubber was 41 W/am³ (1.54 hp/1000 acfm). A cooling tower supplying chilled water to the prescrubber required an additional 26 W/am² (0.96 hp/1000 acfm) for a total system input of 67 W/am³ (2.5 hp/1000 acfm). It is recommended that the scrubber be considered where practical for the removal of fine particulate matter.     

Case studies of scenario analysis for adaptive management of natural resource and infrastructure systems

Management of natural resources and infrastructure systems for sustainability is complicated by uncertainties in the human and natural environment. Moreover, decisions are further complicated by contradictory views, values, and concerns that are rarely made explicit. Scenario analysis can play a major role in addressing the challenges of sustainability management, especially the core question of how to scan the future in a structured, integrated, participatory, and policy-relevant manner. In a context of systems engineering, scenario analysis can provide an integrated and timely understanding of emergent conditions and help to avoid regret and belated action. The purpose of this paper is to present several case studies in natural resources and infrastructure systems management where scenario analysis has been used to aide decision making under uncertainty. The case studies include several resource and infrastructure systems: (1) water resources (2) land-use corridors (3) energy infrastructure, and (4) coastal climate change adaptation. The case studies emphasize a participatory approach, where scenario analysis becomes a means of incorporating diverse stakeholder concerns and experience. This approach to scenario analysis provides insight into both high-performing and robust initiatives/policies, and, perhaps more importantly, influential scenarios. Identifying the scenarios that are most influential to policy making helps to direct further investigative analysis, modeling, and data-collection efforts to support the learning process that is emphasized in adaptive management.     

Mercury body burdens in Gambusia holbrooki and Erimyzon sucetta in a wetland mesocosm amended with sulfate

This study used an experimental model of a constructed wetland to evaluate the risk of mercury methylation when the soil is amended with sulfate. The model was planted with Schoenoplectus californicus and designed to reduce copper, mercury, and metal-related toxicity in a wastestream. The sediments of the model were varied during construction to provide a control and two levels of sulfate treatment, thus allowing characterization of sulfate's effect on mercury methylation and bioaccumulation in periphyton and two species of fish--eastern mosquitofish (Gambusia holbrooki) and lake chubsucker (Erimyzon sucetta). After one year in the experimental model, mean dry-weight normalized total mercury concentrations in mosquitofish from the non-sulfate treated controls (374+/-77 ng/g) and the reference location (233+/-17 ng/g) were significantly lower than those from the low and high sulfate treatments (520+/-73 and 613+/-80 ng/g, respectively). For lake chubsucker, mean total mercury concentration in fish from the high sulfate treatment (276+/-63 ng/g) was significantly elevated over that observed in the control (109+/-47 ng/g), the low sulfate treatment (122+/-42 ng/g), and the reference population (41+/-2 ng/g). Mercury in periphyton was mostly inorganic as methylmercury ranged from 6.6 ng/g (dry weight) in the control to 9.8 ng/g in the high sulfate treatment, while total mercury concentrations ranged from 1147 ng/g in the control to a high of 1297 ng/g in the low sulfate treatment. Fish methylmercury bioaccumulation factors from sediment ranged from 52 to 390 and from 495 to 3059 for water. These results suggest that sulfate treatments add a factor of risk due to elevated production of methylmercury in sediment and porewater which biomagnified into small fish, and may potentially increase through the food web.     

Identifying fecal pollution sources using 3M™ Petrifilm™ count plates and antibiotic resistance analysis in the Horse Creek Watershed in Aiken County,SC (USA)

Sources of fecal coliform pollution in a small South Carolina (USA) watershed were identified using inexpensive methods and commonly available equipment. Samples from the upper reaches of the watershed were analyzed with 3M^? Petrifilm^? count plates. We were able to narrow down the study’s focus to one particular tributary, Sand River, that was the major contributor of the coliform pollution (both fecal and total) to a downstream reservoir that is heavily used for recreation purposes. Concentrations of total coliforms ranged from 2,400 to 120,333 cfu/100 mL, with sharp increases in coliform counts observed in samples taken after rain events. Positive correlations between turbidity and fecal coliform counts suggested a relationship between fecal pollution and stormwater runoff. Antibiotic resistance analysis (ARA) compared antibiotic resistance profiles of fecal coliform isolates from the stream to those of a watershed-specific fecal source library (equine, waterfowl, canines, and untreated sewage). Known fecal source isolates and unknown isolates from the stream were exposed to six antibiotics at three concentrations each. Discriminant analysis grouped known isolates with an overall average rate of correct classification (ARCC) of 84.3 %. A total of 401 isolates from the first stream location were classified as equine (45.9 %), sewage (39.4 %), waterfowl (6.2 %), and feline (8.5 %). A similar pattern was observed at the second sampling location, with 42.6 % equine, 45.2 % sewage, 2.8 % waterfowl, 0.6 % canine, and 8.8 % feline. While there were slight weather-dependent differences, the vast majority of the coliform pollution in this stream appeared to be from two sources, equine and sewage. This information will contribute to better land use decisions and further justify implementation of low-impact development practices within this urban watershed.     

Autonomous real-time adaptive management of soil salinity using a receding horizon control algorithm: a pilot-scale demonstration

Soil salinization is a potentially negative side effect of irrigation with reclaimed water. While optimization schemes have been applied to soil salinity control, these have typically failed to take advantage of real-time sensor feedback. This study incorporates current soil observation technologies into the optimal feedback-control scheme known as Receding Horizon Control (RHC) to enable successful autonomous control of soil salinization. RHC uses real-time sensor measurements, physically-based state prediction models, and optimization algorithms to drive field conditions to a desired environmental state by manipulating application rate or irrigation duration/frequency. A simulation model including the Richards equation coupled to energy and solute transport equations is employed as a state estimator. Vertical multi-sensor arrays installed in the soil provide initial conditions and continuous feedback to the control scheme. An optimization algorithm determines the optimal irrigation rate or frequency subject to imposed constraints protective of soil salinization. A small-scale field test demonstrates that the RHC scheme is capable of autonomously maintaining specified salt levels at a prescribed soil depth. This finding suggests that, given an adequately structured and trained simulation model, sensor networks, and optimization algorithms can be integrated using RHC to autonomously achieve water reuse and agricultural objectives while managing soil salinization.