A land use regression model for predicting ambient volatile organic compound concentrations in Toronto,Canada

More than 25 studies have employed land use regression (LUR) models to estimate nitrogen oxides and to a lesser extent particulate matter indicators, but these methods have been less commonly applied to ambient concentrations of volatile organic compounds (VOCs). Some VOCs have high plausibility as sources of health effects and others are specific indicators of motor vehicle exhaust. We used LUR models to estimate spatial variability of VOCs in Toronto, Canada. Benzene, n-hexane and total hydrocarbons (THC) were measured from July 25 to August 9, 2006 at 50 locations using the TraceAir organic vapor monitors. Nitrogen dioxide (NO₂) was also sampled to assess its spatial pattern agreement with VOC exposures. Buffers for land use, population density, traffic density, physical geography, and remote sensing measures of greenness and surface brightness were also tested. The remote sensing measures have the highest correlations with VOCs and NO₂ levels (i.e., explains >36% of the variance). Our regression models explain 66–68% of the variance in the spatial distribution of VOCs, compared to 81% for the NO₂ model. The ranks of agreement between various VOCs range from 48 to 63% and increases substantially – up to 75% – for the top and bottom quartile groups. Agreements between NO₂ and VOCs are much smaller with an average rank of 36%. Future epidemiologic studies may therefore benefit from using VOCs as potential toxic agents for traffic-related pollutants.     

Estimation and characterization of children’s ambient generated exposure to PM2.5 using sulphate and elemental carbon as tracers

Children’s exposures to ambient and non-ambient fine particulate matter (PM_2.5) were determined using the sulphate and elemental carbon components of the PM_2.5 mixture as tracers of the ambient contribution during a 6-week winter period in Prince George, British Columbia, Canada. Personal exposures to PM_2.5 were measured in children at 5 elementary schools located throughout the city and ambient samples were collected on school rooftops. Average ambient levels and personal exposures during this time period were 13.8 μg m^?3 and 16.4 μg m^?3 respectively. From the data pooled across individuals, use of the two different tracers indicated identical estimates of median exposure to ambient PM_2.5 (7.5 μg m^?3) and similar estimates of non-ambient generated exposure (6.4 and 5.0 μg m^?3) and infiltration (0.49 and 0.52) for the sulphate and elemental carbon approach, respectively. The median fraction of the ambient concentration resulting in exposure or exposure factors were 0.54 and 0.55 respectively, however lower values of 0.46 and 0.42 were determined from regression analysis. A strong association was found between exposure to ambient PM_2.5 and measured ambient concentrations at both the closest school monitor (median r = 0.92) and a central site (median r = 0.88) demonstrating that the central site monitor was suitable for assessing longitudinal ambient generated exposure throughout the city. These results support the use of elemental carbon as a tracer of ambient generated exposure and the use of ambient data as estimates of longitudinal changes in children’s exposure in this setting. The importance of both ambient and non-ambient sources of PM_2.5 is emphasized by their almost equal contribution to total personal exposures. Comparison with other studies suggests a limited influence of climate and the cold season in Prince George on exposure levels and found similar mean non-ambient generated exposures despite large variability across and within subjects in any given location.     

A simplified approach to the indirect evaluation of the chemical composition of atmospheric aerosols from PM mass concentrations

The present work shows a straightforward procedure to indirectly estimate the chemical composition at a given site only from the determination of the PM concentrations, and the classification of the days according to the main meteorological scenarios. A previous study based on the mean chemical composition associated to the main meteorological scenarios is required.This experiment has been carried out with data from two monitoring sites in the North-Western Mediterranean, one regional and one suburban background. At both sites, one-year datasets on chemical PM₁₀ composition were obtained. Based on these datasets, the mean PM₁₀ compositions according to the most relevant meteorological situations were calculated for both locations. After that, the reconstruction of the chemical composition for all the days with available PM₁₀ concentrations was completed. Subsequently, the estimated PM₁₀ composition was compared with that determined experimentally. The comparison between the rebuilt and the experimental results was very satisfactory in the case of the regional background site, and relatively replaced in the other case. Furthermore, the validation of the method at the regional background site has been conducted from the reconstruction of a 4-year data base, and subsequent comparison with the experimental chemical composition.Our results show that it is possible to attain a good approach to the chemical composition at regional background sites, where local emission sources are negligible. Conversely, when the local sources rise in importance, i.e., at a suburban background site, the approach is suitable only for those components with a more regional origin and/or those from long range transport of air masses.     

Relationships Between Nitrogen Transformation Rates and Gene Abundance in a Riparian Buffer Soil

Denitrification is a critical biogeochemical process that results in the conversion of nitrate to volatile products, and thus is a major route of nitrogen loss from terrestrial environments. Riparian buffers are an important management tool that is widely utilized to protect water from non-point source pollution. However, riparian buffers vary in their nitrate removal effectiveness, and thus there is a need for mechanistic studies to explore nitrate dynamics in buffer soils. The objectives of this study were to examine the influence of specific types of soluble organic matter on nitrate loss and nitrous oxide production rates, and to elucidate the relationships between these rates and the abundances of functional genes in a riparian buffer soil. Continuous-flow soil column experiments were performed to investigate the effect of three types of soluble organic matter (citric acid, alginic acid, and Suwannee River dissolved organic carbon) on rates of nitrate loss and nitrous oxide production. We found that nitrate loss rates increased as citric acid concentrations increased; however, rates of nitrate loss were weakly affected or not affected by the addition of the other types of organic matter. In all experiments, rates of nitrous oxide production mirrored nitrate loss rates. In addition, quantitative polymerase chain reaction (qPCR) was utilized to quantify the number of genes known to encode enzymes that catalyze nitrite reduction (i.e., nirS and nirK) in soil that was collected at the conclusion of column experiments. Nitrate loss and nitrous oxide production rates trended with copy numbers of both nir and 16s rDNA genes. The results suggest that low-molecular mass organic species are more effective at promoting nitrogen transformations than large biopolymers or humic substances, and also help to link genetic potential to chemical reactivity.     

Sustainability and emerging issues in scholarly (self-)publishing

In American academic circles, peer-reviewed hard-copy book publishing remains a crucial part of the tenure and promotion process as well as a method of bestowing prestige upon authors accepted by university presses and other mainstream venues. Although a few respected individuals self-published as early as the seventeenth century, the emergence of desktop publishing during the 1980s led to hard-copy and virtual (self-)publishing venues of several kinds, including PDF formatting and the establishment of POD (print on demand) firms. Online, PDF, POD printing, and other challenges to traditional academic publishing can save money and improve efficiency as well as help sustain our forests and other natural resources.     

Addressing climate change: Determinants of consumers' willingness to act and to support policy measures

Consumers influence climate change through their consumption patterns and their support or dismissal of climate mitigation policy measures. Both climate-friendly actions and policy support comprise a broad range of options, which vary in manifold ways and, therefore, might be influenced by different factors. The aims of the study were, therefore, two-fold: first, we intended to find a meaningful way to classify different ways of addressing climate change. Second, we aimed to examine which determinants influence people's willingness to engage in these behaviors. We conducted a large-scale mail survey in Switzerland in which respondents rated, among other items, their willingness to act or support a range of possible actions and mitigations measures. A principal component analysis indicated that a distinction in terms of a behavior's directness as well as a differentiation according to perceived costs seem to be appropriate to classify climate-friendly actions. Multiple regression analyses showed that perceived costs and perceived climate benefit turned out to be the strongest predictors for willingness to act or to support climate policy measures. The strong influence of perceived climate benefit might reflect a strategy of reducing cognitive dissonance. As high-cost behaviors are more difficult to adopt, consumers may reduce dissonance by dismissing high-cost behaviors as not effective in terms of climate mitigation. Political affiliation proved to be another strong determinant of willingness to act or support. Participants on the right wing were less willing to show indirect climate-friendly behaviors, change their mobility behaviors, and to support any type of climate mitigation policy measures. Climate-friendly low-cost behaviors, however, were not influenced by political affiliation.     

Exposure Times to the Spring Atrazine Flush Along a Stream-Reservoir System1

Stoeckel, James A., Jade Morris, Elizabeth Ames, David C. Glover, Michael J. Vanni, William Renwick, and María J. González, 2012. Exposure Times to the Spring Atrazine Flush Along a Stream-Reservoir System. Journal of the American Water Resources Association (JAWRA) 48(3): 616-634. DOI: 10.1111/j.1752-1688.2011.00633.x Abstract: We used enzyme-linked immunosorbent assay to examine reservoir-mediated shifts in spring to fall exposure of aquatic organisms to the spring atrazine pulse over four years in a Midwestern stream-reservoir system. Peak atrazine concentrations in the major inflowing stream exceeded 10 μg/l in all four years. The reservoir had a beneficial effect in two of four years by diluting atrazine below the 10 μg/l threshold. However, during the other two years, exposure times above 10 μg/l were approximately doubled in the reservoir compared to the major inflowing stream. Thresholds of 3 and 5 μg/l were exceeded during all four years in the reservoir. The uplake and downlake reservoir sites were four to five times more likely to exceed these thresholds and aquatic organisms were subjected to longer exposure times above these thresholds compared to the inflowing stream. Release of elevated atrazine concentrations from the reservoir extended exposure times in the outflowing stream. This effect was most pronounced just below the dam. Aquatic organisms upstream of the reservoir were most likely to experience acute exposures whereas organisms within and immediately downstream of the reservoir were more likely to experience chronic exposures. The ubiquity of reservoirs and the annual spring herbicide flush highlight the importance of considering the presence and relative location of reservoirs when assessing risk to aquatic communities as well as locations of drinking water intakes.     

Effects of law enforcement and community outreach on mammal diversity in a biodiversity hotspot

Management activities such as law enforcement and community outreach are thought to affect conservation outcomes in protected areas, but their importance relative to intrinsic environmental characteristics of the parks and extrinsic human pressures surrounding the parks have not been explored. Furthermore, it is not clear which is more related to conservation outcomes—the management itself or local people's perceptions of the management. We measured objective (reports by park staff) and subjective (reports by local people) levels of community outreach and law enforcement based on responses to 374 questionnaires. We estimated mammal abundance and diversity of 6 protected areas based on data from 115 camera traps in Xishuangbanna, southwest China, a biodiversity hotspot with high hunting and land-conversion pressures. We then examined correlations among them and found that local people's perception of law enforcement was positively related to the local abundance of 2 large, hunted species, wild boar (Sus scrofa) (β = 15.22) and muntjac (Muntiacus vaginalis) (β = 14.82), but not related to the abundance of smaller mammals or to objective levels of enforcement. The subjective frequency of outreach by park staff to local communities (β = 3.42) and park size (β = 3.28) were significantly and positively related to mammal species richness, whereas elevation, human population density, and subjective frequency of law enforcement were not. We could not conclude that community outreach and law enforcement were directly causing increased mammal abundance and diversity. Nevertheless, the patterns we detected are some of the first empirical evidence consistent with the idea that biodiversity in protected areas may be more positively and strongly related to local perceptions of the intensity of park management than to either intrinsic (e.g., elevation, park size) or extrinsic (e.g., human population density) environmental factors.     

Cautioning against overemphasis of normative constructs in conservation decision making

Questions around how to conserve nature are increasingly leading to dissonance in conservation planning and action. While science can assist in unraveling the nature of conservation challenges, conservation responses rely heavily on normative positions and constructs to order actions, aid interpretations, and provide motivation. However, problems can arise when norms are mistaken for science or when they stymy scientific rigor. To highlight these potential pitfalls, we used the ethics-based tool of argument analysis to assess a controversial conservation intervention, the Pelorus Island Goat Control Program. The program proponents' argument for restorative justice was unsound because it relied on weak logical construction overly entrenched in normative assumptions. Overreliance on normative constructs, particularly the invocation of tragedy, creates a sense of urgency that can subvert scientific and ethical integrity, obscure values and assumptions, and increase the propensity for flawed logic. This example demonstrates how the same constructs that drive biodiversity conservation can also drive poor decision making, spur public backlash, and justify poor animal welfare outcomes. To provide clarity, a decision-making flowchart we devised demonstrates how values, norms, and ethics influence one another. We recommend practitioners follow 3 key points to improve decision making: be aware of values, as well as normative constructs and ethical theories that those values inform; be mindful of overreliance on either normative constructs or ethics when deciding action is justified; and be logically sound and transparent when building justifications. We also recommend 5 key attributes that practitioners should be attentive to when making conservation decisions: clarity, transparency, scientific integrity, adaptiveness, and compassion. Greater attention to the role of norms in decision making will improve conservation outcomes and garner greater public support for actions.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.