Unlock the Volume: Towards a Politics of Capacity

In recent years “volume” has become a key analytic idea, and tool, for re‐imagining and making sense of historical and contemporary socio‐cultural and geopolitical phenomena. This paper argues that this important work could be pushed in new directions by thinking seriously of how volume might otherwise be interpreted spatially, as capacity . Accordingly, in this paper, we address what we call a “politics of capacity”. To do so, we draw specifically on debates in carceral geography and, in particular, the pressures on the prison system to illustrate our argument. Drawing on notions of “operational capacities” and “capacity building” in the prison setting, we outline a manifesto for volumetric thinking that moves beyond expressions of power that cut through height, depth and angles, to an understanding of how power is conveyed through maximum and minimum capacities; density and mass; and capacity‐building techniques

An Economics-Based Second Law Efficiency

Second Law efficiency is a useful parameter for characterizing the energy requirements of a system in relation to the limits of performance prescribed by the Laws of Thermodynamics. However, since energy costs typically represent less than 50% of the overall cost of product for many large-scale plants (and, in particular, for desalination plants), it is useful to have a parameter that can characterize both energetic and economic effects. In this paper, an economics-based Second Law efficiency is defined by analogy to the exergetic Second Law efficiency and is applied to several desalination systems. It is defined as the ratio of the minimum cost of producing a product divided by the actual cost of production. The minimum cost of producing the product is equal to the cost of the primary source of energy times the minimum amount of energy required, as governed by the Second Law. The analogy is used to show that thermodynamic irreversibilities can be assigned costs and compared directly to non-energetic costs, such as capital expenses, labor and other operating costs. The economics-based Second Law efficiency identifies costly sources of irreversibility and places these irreversibilities in context with the overall system costs. These principles are illustrated through three case studies. First, a simple analysis of multistage flash and multiple effect distillation systems is performed using available data. Second, a complete energetic and economic model of a reverse osmosis plant is developed to show how economic costs are influenced by energetics. Third, a complete energetic and economic model of a solar powered direct contact membrane distillation system is developed to illustrate the true costs associated with so-called free energy sources.Center for Clean Water and Clean Energy at MIT and KFUPM (Project R13-CW-10

Recent Progress in Assessment of Resource Efficiency and Environmental Impacts Embodied in Trade: An Introduction to this Special Issue

This paper serves as an introduction to this special issue on the use of multiregional input- output modeling in assessments of natural resource use and resource use efficiency. Due to globalization, growth in trade has outpaced growth in global gross domestic product (GDP). As a consequence, impacts of consumption of a country increasingly take place abroad. Various methods have been developed to perform so-called footprint analyses. We argue that global multiregional input-output (GMRIO) analysis has the largest potential to provide a consistent accounting framework to calculate a variety of different footprint indicators. The state of the art in GMRIO has, however, various shortcomings, such as limited sector and regional detail and incomplete extensions. The work presented in this special issue addresses a number of such problems and how to possibly overcome them, focusing on the construction of a new GMRIO database (EXIOBASE V3). This database includes long time series in both current and constant prices, a high level of product and sector detail, a physical representation of the world economy, and allows analyzing which footprints out of the many possible indicators provide most information for policy making. Various options for empirical analyses are presented in this special issue. Finally, we analyze how GMRIOs can be further standardized and gradually moved from the scientific to the official statistical domain

A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London

It has long been known that air pollution is harmful to human health, as many epidemiological studies have been conducted into its effects. Collectively, these studies have investigated both the acute and chronic effects of pollution, with the latter typically based on individual level cohort designs that can be expensive to implement. As a result of the increasing availability of small-area statistics, ecological spatio-temporal study designs are also being used, with which a key statistical problem is allowing for residual spatio-temporal autocorrelation that remains after the covariate effects have been removed. We present a new model for estimating the effects of air pollution on human health, which allows for residual spatio-temporal autocorrelation, and a study into the long-term effects of air pollution on human health in Greater London, England. The individual and joint effects of different pollutants are explored, via the use of single pollutant models and multiple pollutant indices

Reconciling timber extraction with biodiversity conservation in tropical forests using reduced-impact logging

Over 20% of the world's tropical forests have been selectively logged, and large expanses are allocated for future timber extraction. Reduced-impact logging (RIL) is being promoted as best practice forestry that increases sustainability and lowers CO2 emissions from logging, by reducing collateral damage associated with timber extraction. RIL is also expected to minimize the impacts of selective logging on biodiversity, although this is yet to be thoroughly tested. We undertake the most comprehensive study to date to investigate the biodiversity impacts of RIL across multiple taxonomic groups. We quantified birds, bats and large mammal assemblage structures, using a before-after control-impact (BACI) design across 20 sample sites over a 5-year period. Faunal surveys utilized point counts, mist nets and line transects and yielded >250 species. We examined assemblage responses to logging, as well as partitions of feeding guild and strata (understorey vs. canopy), and then tested for relationships with logging intensity to assess the primary determinants of community composition. Community analysis revealed little effect of RIL on overall assemblages, as structure and composition were similar before and after logging, and between logging and control sites. Variation in bird assemblages was explained by natural rates of change over time, and not logging intensity. However, when partitioned by feeding guild and strata, the frugivorous and canopy bird ensembles changed as a result of RIL, although the latter was also associated with change over time. Bats exhibited variable changes post-logging that were not related to logging, whereas large mammals showed no change at all. Indicator species analysis and correlations with logging intensities revealed that some species exhibited idiosyncratic responses to RIL, whilst abundance change of most others was associated with time. Synthesis and applications. Our study demonstrates the relatively benign effect of reduced-impact logging (RIL) on birds, bats and large mammals in a neotropical forest context, and therefore, we propose that forest managers should improve timber extraction techniques more widely. If RIL is extensively adopted, forestry concessions could represent sizeable and important additions to the global conservation estate – over 4 million km2

Functional response of U.S. grasslands to the early 21st-century drought

Grasslands across the United States play a key role in regional livelihood and national food security. Yet, it is still unclear how this important resource will respond to the prolonged warm droughts and more intense rainfall events predicted with climate change. The early 21st-century drought in the southwestern United States resulted in hydroclimatic conditions that are similar to those expected with future climate change. We investigated the impact of the early 21st-century drought on aboveground net primary production (ANPP) of six desert and plains grasslands dominated by C4 (warm season) grasses in terms of significant deviations between observed and expected ANPP. In desert grasslands, drought-induced grass mortality led to shifts in the functional response to annual total precipitation (PT), and in some cases, new species assemblages occurred that included invasive species. In contrast, the ANPP in plains grasslands exhibited a strong linear function of the current-year PT and the previous-year ANPP, despite prolonged warm drought. We used these results to disentangle the impacts of interannual total precipitation, intra-annual precipitation patterns, and grassland abundance on ANPP, and thus generalize the functional response of C4 grasslands to predicted climate change. This will allow managers to plan for predictable shifts in resources associated with climate change related to fire risk, loss of forage, and ecosystem services. © 2014 by the Ecological Society of America

Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals