Evaluating the BANCS Streambank Erosion Framework on the Northern Gulf of Mexico Coastal Plain

The Bank Assessment of Nonpoint source Consequences of Sediment (BANCS) framework allows river scientists to predict annual sediment yield from eroding streambanks within a hydrophysiographic region. BANCS involves field data collection and the calibration of an empirical model incorporating a bank erodibility hazard index (BEHI) and near‐bank shear stress (NBS) estimate. Here we evaluate the applicability of BANCS to the northern Gulf of Mexico coastal plain, a region that has not been previously studied in this context. Erosion rates averaged over two years expressed the highest variability of any existing BANCS study. As a result, four standard BANCS models did not yield statistically significant correlations to measured erosion rates. Modifications to two widely used NBS estimates improved their correlations (r² = 0.31 and r² = 0.33), but further grouping of the data by BEHI weakened these correlations. The high variability in measured erosion rates is partly due to the regional hydrologic and climatic characteristics of the Gulf coastal plains, which include large, infrequent precipitation events. Other sources of variability include variations in bank vegetation and the complex hydro‐ and morphodynamics of meandering, sand bed channels. We discuss directions for future research in developing a streambank erosion model for this and similar regions.     

Turn down the heat: regional climate change impacts on development

Regional Environmental Change -     

Who is the Adolescent Environmentalist? Environmental Attitudes,Identity, Media Usage and Communication Orientation

There has been an increase in scholarly attention to adolescents’ environmental attitudes; however, only a small number of empirical studies address the Adolescent Environmentalist’s (AE) personal and collective identity, media usage, and communication orientation. In this study, we investigate differences in young people (aged 12–17) who identify themselves as environmentalists, or the AEs, and those who do not drawing from a national sample of 1096 youth. Results show AEs significantly differ from their peers. The AEs have a different environmental value set, report greater self-confidence and influence among peers, support the stronger display of citizenship behaviors, follow certain news topics more, use and discuss the news more with a variety of others, and report engaging in more dialogue and persuasion.     

Many pathways toward sustainability: not conflict but co-learning between transition narratives

Sustainability transitions aim to comprehensively address key challenges of today’s societies through harmonizing ecological integrity and social viability. During the last decades, increasing attention has focused on the conceptual development and identification of trajectories that navigate societies toward sustainability. While a broad agreement exists with regard to the need for mainstreaming sustainability into the core of decision-making and everyday practices, different transition pathway narratives are advocated to foster urgently needed structural and societal changes. In this article, we describe four archetypes of present transition narratives, examining the system properties (from underpinning intent to mechanistic parameters) that each narrative seeks to transform. We review the articulated critiques of, and provide exemplary case studies for, each narrative. The four transition narratives are (1) the green economy, (2) low-carbon transformation, (3) ecotopian solutions and (4) transition movements. Based on our analysis, we argue that despite the assumption that these narratives represent competing pathways, there is considerable complementarity between them regarding where in a given system they seek to intervene. An integrative approach could potentially help bridge these intervention types and connect fragmented actors at multiple levels and across multiple phases of transition processes. Effectively mainstreaming sustainability will ultimately require sustainability scientists to navigate between, and learn from, multiple transition narratives.     

Recommendations on statistics and benchmarks to assess photochemical model performance

Photochemical grid models are addressing an increasing variety of air quality related issues, yet procedures and metrics used to evaluate their performance remain inconsistent. This impacts the ability to place results in quantitative context relative to other models and applications, and to inform the user and affected community of model uncertainties and weaknesses. More consistent evaluations can serve to drive improvements in the modeling process as major weaknesses are identified and addressed. The large number of North American photochemical modeling studies published in the peer-reviewed literature over the past decade affords a rich data set from which to update previously established quantitative performance “benchmarks” for ozone and particulate matter (PM) concentrations. Here we exploit this information to develop new ozone and PM benchmarks (goals and criteria) for three well-established statistical metrics over spatial scales ranging from urban to regional and over temporal scales ranging from episodic to seasonal. We also recommend additional evaluation procedures, statistical metrics, and graphical methods for good practice. While we primarily address modeling and regulatory settings in the United States, these recommendations are relevant to any such applications of state-of-the-science photochemical models. Our primary objective is to promote quantitatively consistent evaluations across different applications, scales, models, model inputs, and configurations. The purpose of benchmarks is to understand how good or poor the results are relative to historical model applications of similar nature and to guide model performance improvements prior to using results for policy assessments. To that end, it also remains critical to evaluate all aspects of the model via diagnostic and dynamic methods. A second objective is to establish a means to assess model performance changes in the future. Statistical metrics and benchmarks need to be revisited periodically as model performance and the characteristics of air quality change in the future.

Implications: We address inconsistent procedures and metrics used to evaluate photochemical model performance, recommend a specific set of statistical metrics, and develop updated quantitative performance benchmarks for those metrics. We promote quantitatively consistent evaluations across different applications, scales, models, inputs, and configurations, thereby (1) improving the user’s ability to quantitatively place results in context and guide model improvements, and (2) better informing users, regulators, and stakeholders of model uncertainties and weaknesses prior to using results for policy assessments. While we primarily address U.S. modeling and regulatory settings, these recommendations are relevant to any such applications of state-of-the-science photochemical models.     

In Vivo and In Vitro Degradation Studies for Poly(3-hydroxybutyrate-<Emphasis Type="Italic">co</Emphasis>-3-hydroxyhexanoate) Biopolymer

Studies have shown that the copolymer poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) [P(HB-co-HHx)] possesses favorable mechanical properties for use in medical supplies and products (e.g., sutures, scaffolds, bone plates). One of the major under-addressed issues associated with the use of biodegradable, bio-based PHA polymers in resorbable medical products is the correlation between the mechanical properties and the in vivo material degradation over time. In this study, P(HB-co-17 mol% HHx) matrices were mechanically tested after either incubation in cultures of human embryonic kidney cells (HEK) for in vitro degradation studies for up to 4 weeks, or inserted into Danio rerio (zebrafish) tissues for in vivo degradation studies for up to 7 weeks. The mechanical properties and scanning electron microscopy (SEM) images of the degraded materials were examined and later correlated to understand the degradation phenomenon. Our results show that Young’s modulus of P(HB-co-17 mol%HHx) during in vitro studies decreased from 3.26 to 2.42 GPa within 4 weeks, and in vivo breakdown resulted in a significant decrease in Young’s modulus with a decrease from 3.26 to 0.51 GPa and a mass loss of 59 % within 7 weeks. SEM images showed the development of pores and cracks on the surface of the material over time. Plasticization and recrystallization were observed and likely play a role in the alteration of mechanical properties.     

Climate Zone Delineation: Evaluating Approaches for Use in Natural Resource Management

Recent efforts by the United States Department of the Interior (DOI) have the potential to make climate zones the basic geographic units guiding monitoring and resource management programs in the western U.S. We evaluated a new National Park Service approach for delineating climate zones that will likely be a model for other DOI agencies. Using the test case of the Greater Yellowstone Area in Wyoming, Montana and Idaho, we conducted three separate analyses, each based on a different dataset. Cluster analysis of 1971–2000 temperature and precipitation normals grouped weather stations according to similarities in seasonal patterns. Principal Components Analysis (PCAs) of 1895–2008 monthly data grouped stations by similarities in long-term variability. Finally, an analysis of snow data further subdivided the zones defined by the other two analyses. The climate zones produced by the cluster analysis and the PCAs were roughly similar to each other, but the differences were significant. The two sets of zones may be useful for different applications. For example, studies that analyze links between climate patterns and the demography of threatened species should focus on the results of the PCAs. The broad similarity among results produced by the different approaches supported the application of these zones in climate-related monitoring and analysis. However, since choices in data and methodology can affect the details of maps depicting zone boundaries, there are practical limitations to their use.     

Field Measurements of Particulate Matter Emissions,Carbon Monoxide,and Exhaust Opacity from Heavy-Duty Diesel Vehicles

ABSTRACT

Diesel particulate matter (PM) is a significant contributor to ambient air PM₁₀ and PM_2.5 particulate levels. In addition, recent literature argues that submicron diesel PM is a pulmonary health hazard. There is difficulty in attributing PM emissions to specific operating modes of a diesel engine, although it is acknowledged that PM production rises dramatically with load and that high PM emissions occur during rapid load increases on turbocharged engines. Snap-acceleration tests generally identify PM associated with rapid transient operating conditions, but not with high load. To quantify the origin of PM during transient engine operation, continuous opacity measurements have been made using a Wager 650CP full flow exhaust opacity meter. Opacity measurements were taken while the vehicles were operated over transient driving cycles on a chassis dynamometer using the West Virginia University (WVU) Transportable Heavy Duty Vehicle Emissions Testing Laboratories. Data were gathered from Detroit Diesel, Cummins, Caterpillar, and Navistar heavy-duty (HD) diesel engines. Driving cycles used were the Central Business District (CBD) cycle, the WVU 5-Peak Truck cycle, the WVU 5-Mile route, and the New York City Bus (NYCB) cycle. Continuous opacity measurements, integrated over the entire driving cycle, were compared to total integrated PM mass. In addition, the truck was subjected to repeat snap-acceleration tests, and PM was collected for a composite of these snap-acceleration tests. Additional data were obtained from a fleet of 1996 New Flyer buses in Flint, MI, equipped with electronically controlled Detroit Diesel Series 50 engines. Again, continuous opacity, regulated gaseous emissions, and PM were measured. The relationship between continuous carbon monoxide (CO) emissions and continuous opacity was noted. In identifying the level of PM emissions in transient diesel engine operation, it is suggested that CO emissions may prove to be a useful indicator and may be used to apportion total PM on a continuous basis over a transient cycle. The projected continuous PM data will prove valuable in future mobile source inventory prediction.     

Characterization of Indoor Particle Sources Using Continuous Mass and Size Monitors

ABSTRACT

A comprehensive indoor particle characterization study was conducted in nine Boston-area homes in 1998 in order to characterize sources of PM in indoor environments. State-of-the-art sampling methodologies were used to obtain continuous PM_2.5 concentration and size distribution particulate data for both indoor and outdoor air. Study homes, five of which were sampled during two seasons, were monitored over week-long periods. Among other data collected during the extensive monitoring efforts were 24hr elemental/organic carbon (EC/OC) particulate data as well as semi-continuous air exchange rates and time-activity information.

This rich data set shows that indoor particle events tend to be brief, intermittent, and highly variable, thus requiring the use of continuous instrumentation for their characterization. In addition to dramatically increasing indoor PM₂₅ concentrations, these data demonstrate that indoor particle events can significantly alter the size distribution and composition of indoor particles. Source event data demonstrate that the impacts of indoor activities are especially pronounced in the ultrafine (d_a < 0.1 um) and coarse (2.5 < d_a < 10 |um) modes. Among the sources of ultrafine particles characterized in this study are indoor ozone/terpene reactions. Furthermore, EC/OC data suggest that organic carbon is a major constituent of particles emitted during indoor source events. Whether exposures to indoor-generated particles, particularly from large short-term peak events, may be associated with adverse health effects will become clearer when biological mechanisms are better known.     

Quantification of Variability and Uncertainty in Lawn and Garden Equipment NOx and Total Hydrocarbon Emission Factors

Abstract

Variability refers to real differences in emissions among multiple emission sources at any given time or over time for any individual emission source. Variability in emissions can be attributed to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation. Uncertainty refers to lack of knowledge regarding the true value of emissions. Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data. Quantitative methods for characterizing both variability and uncertainty are demonstrated and applied to case studies of emission factors for lawn and garden (L&G) equipment engines. Variability was quantified using empirical and parametric distributions. Bootstrap simulation was used to characterize confidence intervals for the fitted distributions. The 95% confidence intervals for the mean grams per brake horsepower/hour (g/hp-hr) emission factors for two-stroke engine total hydrocarbon (THC) and NO_x emissions were from -30 to +41% and from -45 to +75%, respectively. The confidence intervals for four-stroke engines were from -33 to +46% for THCs and from -27 to +35% for NO_x. These quantitative measures of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories (Els).