The geography of global urban greenhouse gas emissions: an exploratory analysis

The purpose of this paper is to describe global urban greenhouse gas emissions by region and sector, examine the distribution of emissions through the urban-to-rural gradient, and identify covariates of emission levels for our baseline year, 2000. We use multiple existing spatial databases to identify urban extent, greenhouse gas emissions (CO₂, N₂O, CH₄ and SF₆) and covariates of emissions in a “top-down” analysis. The results indicate that urban activities are significant sources of total greenhouse gas emissions (36.8 and 48.6 % of total). The urban energy sector accounts for between 41.5 and 66.3 % of total energy emissions. Significant differences exist in the urban share of greenhouse gas emissions between developed and developing countries as well as among source sectors for geographic regions. The 50 largest urban emitting areas account for 38.8 % of all urban greenhouse gas emissions. We find that greenhouse gas emissions are significantly associated with population size, density, growth rates, and per capita income. Finally, comparison of our results to “bottom-up” estimates suggest that this research’s data and techniques are best used at the regional and global scales.     

Field Test of Enhanced Remedial Amendment Delivery Using a Shear‐Thinning Fluid

Heterogeneity of hydraulic properties in aquifers may lead to contaminants residing in lower‐permeability zones where it is difficult to deliver remediation amendments using conventional injection processes. The focus of this study is to examine use of a shear‐thinning fluid (STF) to improve the uniformity of remedial amendment distribution within a heterogeneous aquifer. Previous studies have demonstrated the significant potential of STFs for improving remedial amendment delivery in heterogeneous aquifers, but quantitative evaluation of these improvements from field applications is lacking. A field‐scale test was conducted that compares data from successive injection of a tracer in water followed by injection of a tracer in an STF to evaluate the impact of the STF on tracer distribution uniformity in the presence of permeability contrasts within the targeted injection zone. Data from tracer breakthrough at multiple depth‐discrete monitoring intervals and electrical resistivity tomography (ERT) showed that inclusion of STF in the injection solution improved the distribution of the injected fluid within the targeted treatment zone. One improvement was a reduction in the movement of injected fluids through high‐permeability pathways, as evidenced by slower breakthrough of tracer at monitoring locations where breakthrough in baseline tracer‐only injection data was faster. In addition, STF‐amended injection solutions arrived faster and to a greater extent in monitoring locations within low‐permeability zones. ERT data showed that the STF injection covered a higher percentage of a two‐dimensional cross section within the injection interval between the injection well and a monitoring well about 3 m away.     

Cumulative spatial impact layers: A novel multivariate spatio‐temporal analytical summarization tool

Scientific inquiry often requires analysis of multiple spatio‐temporal datasets, ranging in type and size, using complex multi‐step processes demanding an understanding of GIS theory and software. Cumulative spatial impact layers (CSIL) is a GIS‐based tool that summarizes spatio‐temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi‐format, multi‐source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built‐in flexibility of the CSIL tool allows users to answer a range of spatially driven questions. Example applications are provided in this article to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision‐making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSIL provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses.     

Evaluation of GPS orbit prediction strategies for the IGS Ultra-rapid products

The International GNSS Service (IGS) provides Ultra-rapid GPS & GLONASS orbits every 6 h. Each product is composed of 24 h of observed orbits with predicted orbits for the next 24 h. We have studied how the orbit prediction performance varies as a function of the arc length of the fitted observed orbits and the parameterization strategy used to estimate the empirical solar radiation pressure (SRP) effects. To focus on the dynamical aspects of the problem, nearly ideal conditions have been adopted by using IGS Rapid orbits and known earth rotation parameters (ERPs) as observations. Performance was gauged by comparison with Rapid orbits as truth by examining WRMS and median orbit differences over the first 6-h and the full 24-h prediction intervals, as well as the stability of the Helmert frame alignment parameters. Two versions of the extended SRP orbit model developed by the Centre for Orbit Determination in Europe (CODE) were tested. Adjusting all nine SRPs (offsets plus once-per-revolution sines and cosines in each satellite-centered frame direction) for each satellite shows smaller mean sub-daily, scale, and origin translation differences. On the other hand, eliminating the four once-per-revolution SRP parameters in the sun-ward and the solar panel axis directions yields orbit predictions that are much more rotationally stable. We found that observed arc lengths of 40–45 h produce the most stable and accurate predictions during 2010. A combined strategy of rotationally aligning the 9 SRP results to the 5 SRP frame should give optimal predictions with about 13 mm mean WRMS residuals over the first 6 h and 50 mm over 24 h. Actual Ultra-rapid performance will be degraded due to the unavoidable rotational errors from ERP predictions.     

The influence of large dams building on resettlement in the Upper Mekong River

This paper seeks to quantify the social and economic impact of resettlement based on the physiographic element changes post relocation. We focus on communities affected by the Nuozhadu hydropower project, the largest existing hydropower project on the mainstream of the Upper Mekong River. Soil and meteorological data were collected from the Soil Spatial Database and the China Terrestrial Ecological Information Spatial Meteorology Database, while social and economic data were collected via field surveys. We have three major con- clusions： （1） Communities will be relocated to a new climate and new elevation, moving from a north tropical climate zone under 700 m to a subtropical climate zone above 700 m. （2） Physiographic element changes due to relocation will reduce household economic income. After relocation, the annual family income of the Shidaimao group decreased by 62%; the annual family income of the other 5 study groups （Lasa, Hani, Nochangchangyi, Mengsa, and Dawazi） dropped by 65%. （3） Communities relocated across the study township are 61.1% less connected with their former relatives after relocation while family-to-family free labor exchange, a previous community norm, decreased by 91%. China＇s dam resettlement compensation system focuses on the loss of economic resources after relocation. However, this study finds that the physiographic elements of the relocation sites are an important driver of ensuring economic growth and stability after relocation. As a result, we recommend more attention be paid to physiographic continuity when designing relocation models.