Can intensive management increase carbon storage in forests?

A possible response to increasing atmospheric CO₂ concentration is to attempt to increase the amount of carbon stored in terrestrial vegetation. One approach to increasing the size of the terrestrial carbon sink is to increase the growth of forests by utilizing intensive forest management practices. This article uses data from the literature and from forest growth and yield models to analyze the impact of three management practices on carbon storage: thinning, fertilization, and control of competing vegetation. Using Douglas-fir (Pseudotsuga menziesii) and loblolly pine (Pinus taeda) as example species, results from experiments with computer simulation models suggest that, for these two species, thinning generally does not increase carbon storage and may actually cause a decrease. The exception is thinning of very dense young stands. Fertilization generally increases carbon storage, although the response can be quite variable. The largest gains in carbon storage are likely to come from fertilizing lower-quality sites and from fertilizing thinned or less dense stands. Forests usually show increased growth in response to fertilization over a wide range of ages. Simulation of the growth of loblolly pine indicates that controlling competing vegetation at an early age helps to maximize stand growth and carbon storage. The research described in this article has been funded by the US Environmental Protection Agency. This document has been prepared at the EPA Environmental Research Laboratory in Corvallis, Oregon, through contract number 68-C8-0006 to NSI Technology Inc. It has been subjected to the agency’s peer and administrative review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.     

Impact of Human Activities on Carbon Dioxide (CO<Subscript>2</Subscript>) Emissions: A Statistical Analysis

Summary The balance of evidence suggests a perceptible human influence on global ecosystems. Human activities are affecting the global ecosystem, some directly and some indirectly. If researchers could clarify the extent to which specific human activities affect global ecosystems, they would be in a much better position to suggest strategies for mitigating against the worst disturbances. Sophisticated statistical analysis can help in interpreting the influence of specific human activities on global ecosystems more carefully. This study aims at identifying significant or influential human activities (i.e. factors) on CO₂ emissions using statistical analyses. The study was conducted for two cases: (i) developed countries and (ii) developing countries. In developed countries, this study identified three influential human activities for CO₂ emissions: (i) combustion of fossil fuels, (ii) population pressure on natural and terrestrial ecosystems, and (iii) land use change. In developing countries, the significant human activities causing an upsurge of CO₂ emissions are: (i) combustion of fossil fuels, (ii) terrestrial ecosystem strength and (iii) land use change. Among these factors, combustion of fossil fuels is the most influential human activity for CO₂ emissions both in developed and developing countries. Regression analysis based on the factor scores indicated that combustion of fossil fuels has significant positive influence on CO₂ emissions in both developed and developing countries. Terrestrial ecosystem strength has a significant negative influence on CO₂ emissions. Land use change and CO₂ emissions are positively related, although regression analysis showed that the influence of land use change on CO₂ emissions was still insignificant. It is anticipated, from the findings of this study, that CO₂ emissions can be reduced by reducing fossil-fuel consumption and switching to alternative energy sources, preserving exiting forests, planting trees on abandoned and degraded forest lands, or by planting trees by social/agroforestry on agricultural lands.     

Potential CO2 emission reduction for BF–BOF steelmaking based on optimised use of ferrous burden materials

Currently, the blast furnace (BF) to basic oxygen furnace (BOF) is the dominant steel production route in the steel industry. The direct CO₂ emission in this process system exceeds 1 t of CO₂/t of crude steel produced. Different ferrous burden materials, for instance iron ore and scrap, can be used in various proportions in this steelmaking route. This paper analyses how energy use, conversion costs, and CO₂ emissions can be influenced by the use of different ferrous burden materials when producing crude steel. An optimisation mixed integer linear programming (MILP) model has been applied for analysis. By the use of the optimisation model, it is possible to highlight some issues of special importance, such as best practices to increase production at low conversion cost, or best practices to increase production at low CO₂ emission. It is found out that more benefits will be gained when using the system-oriented analysis to the steelmaking process. Furthermore, a comprehensive view of the trade-offs between the objectives of Cost and CO₂ can provide useful information for decision makers to generate strategies under the future emission trading.     

The role of optimality in characterizing CO2 seepage from geologic carbon sequestration sites

Storage of large amounts of carbon dioxide (CO₂) in deep geologic formations for greenhouse-gas mitigation is gaining momentum and moving from its conceptual and testing stages towards widespread application. In this work we explore various optimization strategies for characterizing surface leakage (seepage) using near-surface measurement approaches such as accumulation chambers and eddy covariance towers. Seepage characterization objectives and limitations need to be defined carefully from the outset especially in light of large natural background variations that can mask seepage. The cost and sensitivity of seepage detection are related to four critical length scales pertaining to the size of the: (1) region that needs to be monitored; (2) footprint of the measurement approach, and (3) main seepage zone; (4) region in which concentrations or fluxes are influenced by seepage. Seepage characterization objectives may include one or all of the tasks of detecting, locating, and quantifying seepage. Each of these tasks has its own optimal strategy. Detecting and locating seepage in a region in which there is no expected or preferred location for seepage nor existing evidence for seepage requires monitoring on a fixed grid, e.g., using eddy covariance towers. The fixed-grid approaches needed to detect seepage are expected to require large numbers of eddy covariance towers for large-scale geologic CO₂ storage. Once seepage has been detected and roughly located, seepage zones and features can be optimally pinpointed through a dynamic search strategy, e.g., employing accumulation chambers and/or soil-gas monitoring. Quantification of seepage rates can be done through measurements on a localized fixed grid once the seepage is pinpointed. Background measurements are essential for seepage detection in natural ecosystems. Artificial neural networks are considered as regression models useful for distinguishing natural system behavior from anomalous behavior suggestive of CO₂ seepage without need for detailed understanding of natural system processes. Because of the local extrema in CO₂ fluxes and concentrations in natural systems, simple steepest-descent algorithms are not effective and evolutionary computation algorithms are proposed as a paradigm for dynamic monitoring networks to pinpoint CO₂ seepage areas.     

Linking carbon sequestration science with local sustainability: an integrated assessment approach

This paper introduces an integrated assessment (IA) approach for a Canada-China joint research project that linked forest carbon sequestration, forest resource management, and local sustainability enhancement. The purpose of the IA was to improve the measurement of carbon in different land uses and vegetation covers, as well as to direct decision makers to those land uses or options as an CO₂ emission reduction strategy while supporting rural sustainable development. In this connection, three questions are addressed in this paper:

1)

How will forestry carbon sequestration land use policies affect regional sustainability prospects in rural China?     

Cocoa Intensification Scenarios and Their Predicted Impact on CO<Subscript>2</Subscript> Emissions,Biodiversity Conservation,and Rural Livelihoods in the Guinea Rain Forest of West Africa

The Guinean rain forest (GRF) of West Africa, identified over 20 years ago as a global biodiversity hotspot, had reduced to 113,000 km² at the start of the new millennium which was 18% of its original area. The principal driver of this environmental change has been the expansion of extensive smallholder agriculture. From 1988 to 2007, the area harvested in the GRF by smallholders of cocoa, cassava, and oil palm increased by 68,000 km². Field results suggest a high potential for significantly increasing crop yields through increased application of seed-fertilizer technologies. Analyzing land-use change scenarios, it was estimated that had intensified cocoa technology, already developed in the 1960s, been pursued in Cote d’Ivoire, Ghana, Nigeria and Cameroon that over 21,000 km² of deforestation and forest degradation could have been avoided along with the emission of nearly 1.4 billion t of CO₂. Addressing the low productivity of agriculture in the GRF should be one of the principal objectives of REDD climate mitigation programs.     

Overview of Contemporary Issues of Forest Research and Management in China

With 207 million ha of forest covering 22% of its land area, China ranks fifth in the world in forest area. Rapid economic growth, climate change, and forest disturbances pose new, complex challenges for forest research and management. Progress in meeting these challenges is relevant beyond China, because China’s forests represent 34% of Asia’s forests and 5% of the worlds’ forests. To provide a broader understanding of these management challenges and of research and policies that address them, we organized this special issue on contemporary forest research and management issues in China. At the national level, papers review major forest types and the evolution of sustainable forestry, the development of China’s forest-certification efforts, the establishment of a forest inventory system, and achievements and challenges in insect pest control in China. Papers focused on Northern China address historical, social, and political factors that have shaped the region’s forests; the use of forest landscape models to assess how forest management can achieve multiple objectives; and analysis and modeling of fuels and fire behavior. Papers addressing Central and South China describe the “Grain for Green” program, which converts low productivity cropland to grassland and woodland to address erosion and soil carbon sequestration; the potential effects of climate change on CO₂ efflux and soil respiration; and relationships between climate and net primary productivity. China shares many forest management and research issues with other countries, but in other cases China’s capacity to respond to forest management challenges is unique and bears watching by the rest of the world.     

Tandem bed configuration for sorption-enhanced steam reforming of methane

The required properties of a CO₂ sorbent for sorption-enhanced steam–methane reforming (SESMR) are derived following a top-down approach. First the required CO₂ equilibrium pressure of the sorbent is derived from system restraints, then a suitable sorbent is searched for matching the required CO₂ pressure. The selected material, barium orthotitanate Ba₂TiO₄, has been characterized and tested on lab-scale. From this follows that the capacity and kinetics are poor compared with CaO, which has been investigated for SESMR. The best use of Ba₂TiO₄ is in combination with CaO, making use of the good properties of both: the high capacity and good kinetics of CaO, and the low CO₂ equilibrium pressure of Ba₂TiO₄ allowing high CH₄ conversion at relatively low steam-to-methane ratios (3–4).