Joint Global Change Research Institute

About: Joint Global Change Research Institute is a facility organization based out in Riverdale Park, Maryland, United States. It is known for research contribution in the topics: Greenhouse gas & Climate change. The organization has 197 authors who have published 934 publications receiving 62390 citations.

The surprisingly inexpensive cost of state-driven emission control strategies

Abstract: Traditionally, analysis of the costs of cutting greenhouse gas emissions has assumed that governments would implement idealized, optimal policies such as uniform economy-wide carbon taxes. Yet actual policies in the real world, especially in large federal governments, are often highly heterogeneous and vary in political support and administrative capabilities within a country. While the benefits of heterogeneous action have been discussed widely for experimentation and leadership, little is known about its costs. Focusing on the United States, we represent plausible variation (by more than a factor of 3) in the stringency of state-led climate policy in a process-based integrated assessment model (GCAM-USA). For a wide array of national decarbonization targets, we find that the nationwide cost from heterogeneous subnational policies is only one-tenth higher than nationally uniform policies. Such results hinge on two critical technologies (advanced biofuels and electricity) for which inter-state trade ameliorates the economic efficiencies that might arise with heterogeneous action. The nationwide cost of cutting emissions can be affected by local policies. This study considers the differences across the US states, with integrated assessment model results showing that varying state policies only increases nationwide costs by about 10%.

Accelerated adoption of carbon dioxide capture and storage Within the United States electric utility industry: The impact of stabilizing at 450 PPMV and 550 PPMV

Abstract: Publisher Summary Conventional wisdom has held that stabilization of atmospheric concentrations of CO2 would likely entail the retirement of a few of the oldest, most obsolete plants in the nation each year, with the majority of emissions abatement coming from the operation of CCS-enabled power plants that were built to serve the needs of a growing economy. But according to the above analysis, following the WRE450 emissions pathway would result in the retirement of 769 plants in the space of 60 years (2005-2064), an average of 13 coal plants per year for six decades, resulting in a nearly complete decommissioning and rebuilding of the entire U.S. coal-fired fleet, with additional turnover in oil- and gas-fired generation. In either the WRE450 or WRE550 case, it is clear that the measures necessary to bring about stabilization of atmospheric concentrations of CO2 for just one sector of the U.S. economy, the electric utility sector, will require a massive effort on the part of industrial and public entities. Even if such a large-scale deployment of CCS within the U.S. electric power sector were to be undertaken, it must be coupled with similar aggressive emissions strategies in all economic sectors and in all nations to have the desired impact of bringing about stabilized atmospheric concentrations of CO2.

The Relationships Between the Trends of Mean and Extreme Precipitation

Abstract: This study provides a better understanding of the relationships between the trends of mean and extreme precipitation in two observed precipitation data sets: the Climate Prediction Center Unified daily precipitation data set and the Global Precipitation Climatology Program (GPCP) pentad data set. The study employs three kinds of definitions of extreme precipitation: (1) percentile, (2) standard deviation and (3) generalize extreme value (GEV) distribution analysis for extreme events based on local statistics. Relationship between trends in the mean and extreme precipitation is identified with a novel metric, i.e. area aggregated matching ratio (AAMR) computed on regional and global scales. Generally, more (less) extreme events are likely to occur in regions with a positive (negative) mean trend. The match between the mean and extreme trends deteriorates for increasingly heavy precipitation events. The AAMR is higher in regions with negative mean trends than in regions with positive mean trends, suggesting a higher likelihood of severe dry events, compared with heavy rain events in a warming climate. AAMR is found to be higher in tropics and oceans than in the extratropics and land regions, reflecting a higher degree of randomness and more important dynamical rather than thermodynamical contributions of extreme events in the latter regions.

The interplay of labile organic carbon, enzyme activities and microbial communities of two forest soils across seasons.

Abstract: Soil labile organic carbon (LOC) responds rapidly to environmental changes and plays an important role in carbon cycle. In this study, the seasonal fluctuations in LOC, the activities of carbon-cycle related enzymes, and the bacterial and fungal communities were analyzed for soils collected from two forests, namely Betula albosinensis (Ba) and Picea asperata Mast. (Pa), in the Qinling Mountains of China. Results revealed that the seasonal average contents of microbial biomass carbon (MBC), easily oxidized organic carbon (EOC), and dissolved organic carbon (DOC) of Pa forest soil were 13.5%, 30.0% and 15.7% less than those in Ba soil. The seasonal average enzyme activities of β-1,4-glucosidase (βG), and β-1,4-xylosidase (βX) of Ba forest soils were 30.0% and 32.3% higher than those of Pa soil while the enzyme activity of cellobiohydrolase (CBH) was 19.7% lower. Furthermore, the relative abundance of Acidobacteria was significantly higher in summer than in winter, whereas the relative abundance of Bacteroidetes was higher in winter. Regarding the fungal communities, the relative abundance of Basidiomycota was lowest in winter, whereas Ascomycota predominated in the same season. In addition, the soil LOC was significantly positively correlated with the CBH, βG and βX activities. Changes in LOC were significantly correlated with Acidobacteria, Bacteroidetes and Basidiomycota. We conclude that the seasonal fluctuations in forest soil LOC fractions relied on carbon cycle-associated enzymatic activities and microorganisms, which in turn were affected by climatic conditions.