Social learning in a policy-mandated collaboration: community wildfire protection planning in the eastern United States

Policies such as the US Healthy Forests Restoration Act (HFRA) mandate collaboration in planning to create benefits such as social learning and shared understanding among partners. However, some question the ability of top-down policy to foster successful local collaboration. Through in-depth interviews and document analysis, this paper investigates social learning and transformative learning in three case studies of Community Wildfire Protection Planning (CWPP), a policy-mandated collaboration under HFRA. Not all CWPP groups engaged in social learning. Those that did learned most about organisational priorities and values through communicative learning. Few participants gained new skills or knowledge through instrumental learning. CWPP groups had to commit to learning, but the design of the collaborative-mandate influenced the type of learning that was most likely to occur. This research suggests a potential role for top-down policy in setting the structural context for learning at the local level, but also confirms the importance of collaborative context and process in fostering social learning.     

The Number-Size Distribution of Atmospheric Particles During Temperature Inversions

Instruments capable of measuring in situ numbers of particles within specific size ranges covering a particle-diameter spectrum of approximately 0.001 – 10 microns have been employed to continuously monitor the concentration and size-distribution of atmospheric aerosols. The monitoring site was a television tower located on the boundary between Minneapolis and St. Paul, Minnesota. Air samples were drawn from 70, 170, and 500 feet above ground level and analyzed with optical, electrical, and condensation particle counters to obtain a number-size distribution within the 0.001 – 10 micron size range. In addition to the measurement of particle number and size, several micrometeorological parameters were simultaneously monitored. Particle number-size distributions which were measured during periods of temperature inversion are reported     

On the Relation Between the Indoor and Outdoor Concentrations of Nitrogen Oxides

Simultaneous measurements were made of the concentrations of NO, NO₂, and CO inside and outside of a building. The building is located in the Los Angeles area, which is heavily polluted by photochemical smog, and the experiments were conducted at a time of the year when the pollutants in question tend to be high. The results shows that there is a direct relationship between the inside and outside concentrations, and that the phase lag between the concentrations depends principally on the ratio of the building volume to the ventilation rate. Although the outside concentrations of the pollutants in question did not follow the same pattern every day, peak concentrations seemed to be related to “rush-hour” traffic. By reducing ventilation rates during these periods, it may be possible to reduce the concentration peaks inside of the building. The building involved in the current study was not located in the immediate vicinity of heavy traffic, and the indoor concentrations of NO, NO₂, and CO did not appear to be very severe when compared to those defined by present air quality standards. Finally, the results support the belief that NO and O₃ do not co-exist indoors except in very small quantities.     

An Evaluation of the Effects of Ozone Injury on Radial Growth of Ponderosa Pine (Pinus ponderosa) in the Southern Sierra Nevada

Growth of ponderosa pines with visible symptoms of ozone injury was compared with that of asymptomatic trees in the southern Sierra Nevada, California. Time series analysis indicated that there was no significant reduction in annual radial increment of symptomatic trees during recent years compared to past growth and growth of asymptomatic trees. First order autocorrelation and climatic variables accounted for a large proportion of the variance in growth index, and winter precipitation was positively correlated with growth for all size and age classes. Although ozone concentrations are high enough to cause chlorosis and premature needle senescence in ponderosa pine, there has been no significant change in growth associated with ozone injury.     

Modeling Atmospheric Mercury Deposition in the Vicinity of Power Plants

Abstract

Two mathematical models of the atmospheric fate and transport of mercury (Hg), an Eulerian grid–based model and a Gaussian plume model, are used to calculate the atmospheric deposition of Hg in the vicinity (i.e., within 50 km) of five coal–fired power plants. The former is applied using two different horizontal resolutions: coarse (84 km) and fine (16.7 km). More than 96% of the power plant Hg emissions are calculated with the plume model to be transported beyond 50 km from the plants. The grid–based model predicts a lower fraction to be transported beyond 50 km: >91% with a coarse resolution and >95% with a fine resolution. The contribution of the power plant emissions to total Hg deposition within a radius of 50 km from the plants is calculated to be <8% with the plume model, <14% with the Eulerian model with a coarse resolution, and <10% with the Eulerian model with a fine resolution. The Eulerian grid–based model predicts greater local impacts than the plume model because of artificially enhanced vertical dispersion; the former predicts about twice as much Hg deposition as the latter when the area considered is commensurate with the resolution of the grid–based model. If one compares the local impacts for an area that is significantly less than the grid–based model resolution, then the grid–based model may predict lower local deposition than the plume model, because two compensating errors affect the results obtained with the grid–based model: initial dilution of the power plant emissions within one or more grid cells and enhanced vertical mixing to the ground.     

Compatible Blends of Zein and Polyvinylpyrrolidone

Blends of zein and polyvinylpyrrolidone (PVP) were compared based on their tensile properties, thermal properties and morphology. Zein was blended with polyvinylpyrrolidone of varying molecular weights (10, 55, and 1,300 kDa) and films were cast from ethanol solutions. Films cast using the higher molecular weight polymers showed an improvement in tensile strength, up to a 24% increase, compared to control. Differential scanning calorimetry data for the blends showed single T_m and T_g values of an intermediate value between those of zein and PVP control samples. Field emission scanning electron microscopy images show no obvious inhomogeneities, and confocal fluorescence microscopy showed no decreased uniformity in the PVP/zein films compared to control. Electrospun fibers of the zein/PVP blends were also obtained. These findings suggest that zein and polyvinylpyrrolidone combine to form a compatible blend, the first such blend of zein with a synthetic polymer.     

Social-ecological system resonance: a theoretical framework for brokering sustainable solutions

Sustainability science is a solution-oriented discipline. Yet, there are few theory-rich discussions about how this orientation structures the efforts of sustainability science. We argue that Niklas Luhmann’s social system theory, which explains how societies communicate problems, conceptualize solutions, and identify pathways towards implementation of solutions, is valuable in explaining the general structure of sustainability science. From Luhmann, we focus on two key concepts. First, his notion of resonance offers us a way to account for how sustainability science has attended and responded to environmental risks. As a product of resonance, we reveal solution-oriented research as the strategic coordination of capacities, resources, and information. Second, Luhmann’s interests in self-organizing processes explain how sustainability science can simultaneously advance multiple innovations. The value logic that supports this multiplicity of self-organizing activities as a recognition that human and natural systems are complex coupled and mutually influencing. To give form to this theoretical framework, we offer case evidence of renewable energy policy formation in Texas. Although the state’s wealth is rooted in a fossil-fuel heritage, Texas generates more electricity from wind than any US state. It is politically antagonistic towards climate-change policy, yet the state’s reception of wind energy technology illustrates how social and environmental systems can be strategically aligned to generate solutions that address diverse needs simultaneously. This case demonstrates that isolating climate change—as politicians do as a separate and discrete problem—is incapable of achieving sustainable solutions, and resonance offers researchers a framework for conceptualizing, designing, and communicating meaningfully integrated actions.     

Analysis of short-term ozone and PM2.5 measurements: Characteristics and relationships for air sensor messaging

Air quality sensors are becoming increasingly available to the general public, providing individuals and communities with information on fine-scale, local air quality in increments as short as 1 min. Current health studies do not support linking 1-min exposures to adverse health effects; therefore, the potential health implications of such ambient exposures are unclear. The U.S. Environmental Protection Agency (EPA) establishes the National Ambient Air Quality Standards (NAAQS) and Air Quality Index (AQI) on the best science available, which typically uses longer averaging periods (e.g., 8 hr; 24 hr). Another consideration for interpreting sensor data is the variable relationship between pollutant concentrations measured by sensors, which are short-term (1 min to 1 hr), and the longer term averages used in the NAAQS and AQI. In addition, sensors often do not meet federal performance or quality assurance requirements, which introduces uncertainty in the accuracy and interpretation of these readings. This article describes a statistical analysis of data from regulatory monitors and new real-time technology from Village Green benches to inform the interpretation and communication of short-term air sensor data. We investigate the characteristics of this novel data set and the temporal relationships of short-term concentrations to 8-hr average (ozone) and 24-hr average (PM_2.5) concentrations to examine how sensor readings may relate to the NAAQS and AQI categories, and ultimately to inform breakpoints for sensor messages. We consider the empirical distributions of the maximum 8-hr averages (ozone) and 24-hr averages (PM_2.5) given the corresponding short-term concentrations, and provide a probabilistic assessment. The result is a robust, empirical comparison that includes events of interest for air quality exceedances and public health communication. Concentration breakpoints are developed for short-term sensor readings such that, to the extent possible, the related air quality messages that are conveyed to the public are consistent with messages related to the NAAQS and AQI.

Implications: Real-time sensors have the potential to provide important information about fine-scale current air quality and local air quality events. The statistical analysis of short-term regulatory and sensor data, coupled with policy considerations and known health effects experienced over longer averaging times, supports interpretation of such short-term data and efforts to communicate local air quality.     

Modeling the Effects of Potential Salinity Shifts on the Recovery of Striped Bass in the Savannah River Estuary,Georgia–South Carolina,United States

Increased salinity in spawning and nursery grounds in the Savannah River estuary was cited as the primary cause of a 97% decrease in adult striped bass (Morone saxatilis) and a concomitant 96% decrease in striped bass egg production. Restoration efforts focused on environmental remediation and stock enhancement have resulted in restored salinity patterns and increased egg and adult abundances. However, future water needs or harbor development may preclude further recovery by reducing freshwater inflow or increasing salinity intrusion. To assess the effect of potential changes in the salinity regime, we developed models relating discharge, tidal phase, and salinity to striped bass egg and early larval survival and re-cast these in a quantitative Bayesian belief network. The model indicated that a small upstream shift (≤1.67 km) in the salinity regime would have the least impact on striped bass early life history survival, whereas shifts >1.67 km would have progressively larger impacts, with a 8.33-km shift potentially reducing our estimated survival probability by >28%. Such an impact could have cumulative and long-term detrimental effects on the recovery of the Savannah River striped bass population. The available salinity data were collected during average and low flows, so our model represents some typical and some extreme conditions during a striped bass spawning season. Our model is a relatively simplistic, “first-order” attempt at evaluating potential effects of changes in the Savannah River estuarine salinity regime and points to areas of concern and potential future research.