Synergistic vulnerabilities: climate variability and fire management policy increase farming challenges in southeastern Mexico

Agricultural fire for land preparation is central in the livelihoods of subsistence farmers practicing shifting cultivation. Achieving a good agricultural burn, one in which the biomass is thoroughly consumed within the chosen area, depends on specific weather conditions. Fire use decisions are also shaped by institutions that define the timing and rules for fire use but also constrain the alternatives and shape adaptive capacities. Global and regional climate changes interact with the institutional framing of fire management affecting local fire use and burn outcomes. These effects are documented and analyzed to suggest adaptations to existing governance systems. We examined subsistence farmers’ socio-ecological vulnerability in the Calakmul municipality, located in southeastern Mexico. Using interviews with farmers and government agents, as well as participatory mapping and observation of agricultural burns, we studied fire management knowledge, practices and burn outcomes. Our results describe a continuum of burn outcomes covering good agricultural burns, uncontrolled burns leading to wildfires and “malquemados” literally poorly burned areas. Malquemados represent unsuccessful combustion associated with excess moisture that results in scorched vegetation. We discuss how unexpected early rains trigger effects that cascade through space and the ecological, economic and cultural domains. We argue that fire management has been historically approached from a conservation standpoint yet agricultural fire use and wildfire prevention should also be addressed from a rural development perspective. This shift in fire management would lead to the proper inclusion of the entire array of burn outcomes in studies and policies addressing farmers’ vulnerability amplified by synergistic effects between climate variability and institutional change.     

Why does the United States lack a global warming policy? The corporate inner circle versus public interest sector elites

Why has the United States not adopted global warming policies? Because the inner circle of the corporate elite has opposed these policies despite some corporate support for cap-and-trade and other policies. Pro- and anti-positions taken by think tanks that have led the policy debate in the post-Kyoto period are analyzed in order to demonstrate this. The corporate and upper class social ties of the directors of these pro- and anti-think tanks are examined, revealing a corporate elite split between the inner circle opposing these policies, and a ‘public interest sector’ of corporate law and media corporations along with top executives from higher education and other nonprofits that is supportive of policies addressing global warming. To enable adoption of major global warming policies, the corporate inner circle will need to become supportive and forge a class-wide corporate consensus on the need to address global warming.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

How Good? Ethical Criteria for a ‘Good Life’ for Farm Animals

The Farm Animal Welfare Council’s concept of a Good Life gives an idea of an animal’s quality of life that is over and above that of a mere life worth living. The concept needs explanation and clarification, in order to be meaningful, particularly for consumers who purchase farm animal produce. The concept could allow assurance schemes to apply the label to assessments of both the potential of each method of production, conceptualised in ways expected to enhance consumers’ engagement such as ‘naturalness’ and ‘freedom’; and the concept of a life worth living as a safeguard threshold below which no animal’s actual welfare should fall, based on each animal’s overall affective states. This may provide a framework for development of the Good Life concept, within scientific and sociological fields, in order to allow reliable and influential use by assessors, consumers and retailers.     

Detention Outlet Retrofit Improves the Functionality of Existing Detention Basins by Reducing Erosive Flows in Receiving Channels

By discharging excess stormwater at rates that more frequently exceed the critical flow for stream erosion, conventional detention basins often contribute to increased channel instability in urban and suburban systems that can be detrimental to aquatic habitat and water quality, as well as adjacent property and infrastructure. However, these ubiquitous assets, valued at approximately $600,000 per km² in a representative suburban watershed, are ideal candidates to aid in reversing such cycles of channel degradation because improving their functionality would not necessarily require property acquisition or heavy construction. The objective of this research was to develop a simple, cost‐effective device that could be installed in detention basin outlets to reduce the erosive power of the relatively frequent storm events (~ < two‐year recurrence) and provide a passive bypass to maintain flood control performance during infrequent storms (such as the 100‐year recurrence). Results from a pilot installation show that the Detain H₂O device reduced the cumulative sediment transport capacity of the preretrofit condition by greater than 40%, and contributed to reduced flashiness and prolonged baseflows in receiving streams. When scaling the strategy across a watershed, these results suggest that potential gains in water quality and stream channel stability could be achieved at costs that are orders of magnitude less than comparable benefits from newly constructed stormwater control measures.     

Matrix Diffusion Modeling Applied to Long‐Term Pump‐and‐Treat Data: 2. Results From Three Sites

The data mining/groundwater modeling methodology developed in McDade et al. (2013) was performed to determine if matrix diffusion is a plausible explanation for the lower‐concentration but persistent chlorinated solvent plumes in the groundwater‐bearing units at three different pump‐and‐treat systems. Capture‐zone maps were evaluated, and eight wells were identified that did not draw water from any of the historical source areas but captured water from the sides of the plume. Two groundwater models were applied to study the persistence of the plumes in the absence of contributions from the historical source zones. In the wells modeled, the observed mass discharge generally decreased by about one order of magnitude or less over 4 to 10 years of pumping, and 1.8 to 17 pore volumes were extracted. In five of the eight wells, the matrix diffusion model fit the data much better than the advection dispersion retardation model, indicating that matrix diffusion better explains the persistent plume. In the three other wells, confounding factors, such as a changing capture zone over time (caused by changes in pumping rates in adjacent extraction wells); potential interference from a high‐concentration unremediated source zone; and limited number of pore volumes removed made it difficult to confirm that matrix diffusion processes were active in these areas. Overall, the results from the five wells indicate that mass discharge rates from the pumping wells will continue to show a characteristic “long tail'' of mass removal from zones affected by active matrix diffusion processes. Future site management activities should include matrix diffusion processes in the conceptual site models for these three sites. © 2013 Wiley Periodicals, Inc.     

An exploratory study of air emissions associated with shale gas development and production in the Barnett Shale

Information regarding air emissions from shale gas extraction and production is critically important given production is occurring in highly urbanized areas across the United States. Objectives of this exploratory study were to collect ambient air samples in residential areas within 61 m (200 feet) of shale gas extraction/production and determine whether a “fingerprint” of chemicals can be associated with shale gas activity. Statistical analyses correlating fingerprint chemicals with methane, equipment, and processes of extraction/production were performed. Ambient air sampling in residential areas of shale gas extraction and production was conducted at six counties in the Dallas/Fort Worth (DFW) Metroplex from 2008 to 2010. The 39 locations tested were identified by clients that requested monitoring. Seven sites were sampled on 2 days (typically months later in another season), and two sites were sampled on 3 days, resulting in 50 sets of monitoring data. Twenty-four-hour passive samples were collected using summa canisters. Gas chromatography/mass spectrometer analysis was used to identify organic compounds present. Methane was present in concentrations above laboratory detection limits in 49 out of 50 sampling data sets. Most of the areas investigated had atmospheric methane concentrations considerably higher than reported urban background concentrations (1.8–2.0 ppm_v). Other chemical constituents were found to be correlated with presence of methane. A principal components analysis (PCA) identified multivariate patterns of concentrations that potentially constitute signatures of emissions from different phases of operation at natural gas sites. The first factor identified through the PCA proved most informative. Extreme negative values were strongly and statistically associated with the presence of compressors at sample sites. The seven chemicals strongly associated with this factor (o-xylene, ethylbenzene, 1,2,4-trimethylbenzene, m- and p-xylene, 1,3,5-trimethylbenzene, toluene, and benzene) thus constitute a potential fingerprint of emissions associated with compression.

Implications: Information regarding air emissions from shale gas development and production is critically important given production is now occurring in highly urbanized areas across the United States. Methane, the primary shale gas constituent, contributes substantially to climate change; other natural gas constituents are known to have adverse health effects. This study goes beyond previous Barnett Shale field studies by encompassing a wider variety of production equipment (wells, tanks, compressors, and separators) and a wider geographical region. The principal components analysis, unique to this study, provides valuable information regarding the ability to anticipate associated shale gas chemical constituents.     

Concentrations of mobile source air pollutants in urban microenvironments

Human exposures to criteria and hazardous air pollutants (HAPs) in urban areas vary greatly due to temporal-spatial variations in emissions, changing meteorology, varying proximity to sources, as well as due to building, vehicle, and other environmental characteristics that influence the amounts of ambient pollutants that penetrate or infiltrate into these microenvironments. Consequently, the exposure estimates derived from central-site ambient measurements are uncertain and tend to underestimate actual exposures. The Exposure Classification Project (ECP) was conducted to measure pollutant concentrations for common urban microenvironments (MEs) for use in evaluating the results of regulatory human exposure models. Nearly 500 sets of measurements were made in three Los Angeles County communities during fall 2008, winter 2009, and summer 2009. MEs included in-vehicle, near-road, outdoor, and indoor locations accessible to the general public. Contemporaneous 1- to 15-min average personal breathing zone concentrations of carbon monoxide (CO), carbon dioxide (CO₂), volatile organic compounds (VOCs), nitric oxide (NO), nitrogen oxides (NO_x), particulate matter (<2.5 μm diameter; PM_2.5) mass, ultrafine particle (UFP; <100 nm diameter) number, black carbon (BC), speciated HAPs (e.g., benzene, toluene, ethylbenzene, xylenes [BTEX], 1,3-butadiene), and ozone (O₃) were measured continuously. In-vehicle and inside/outside measurements were made in various passenger vehicle types and in public buildings to estimate penetration or infiltration factors. A large fraction of the observed pollutant concentrations for on-road MEs, especially near diesel trucks, was unrelated to ambient measurements at nearby monitors. Comparisons of ME concentrations estimated using the median ME/ambient ratio versus regression slopes and intercepts indicate that the regression approach may be more accurate for on-road MEs. Ranges in the ME/ambient ratios among ME categories were generally greater than differences among the three communities for the same ME category, suggesting that the ME proximity factors may be more broadly applicable to urban MEs.

Implications:Estimates of population exposure to air pollutants extrapolated from ambient measurements at ambient fixed site monitors or exposure surrogates are prone to uncertainty. This study measured concentrations of mobile source air toxics (MSAT) and related criteria pollutants within in-vehicle, outdoor near-road, and indoor urban MEs to provide multipollutant ME measurements that can be used to calibrate regulatory exposure models.     

Optimization-Based Atmospheric Plume Source Identification

This work applies optimization and an Eulerian inversion approach presented by Bagtzoglou and Baun in 2005 in order to reconstruct contaminant plume time histories and to identify the likely source of atmospheric contamination using data from a real test site for the first time. Present-day distribution of an atmospheric contaminant plume as well as data points reflecting the plume history allow the reconstruction and provide the plume velocity, distribution, and probable source. The method was tested to a hypothetical case and with data from the Forest Atmosphere Transfer and Storage (FACTS) experiment in the Duke experimental forest site. In the scenarios presented herein, as well as in numerous cases tested for verification purposes, the model conserved mass, successfully located the peak of the plume, and managed to capture the motion of the plume well but underestimated the contaminant peak.