Alternative carbon dioxide modelling approaches accounting for high residual gases in LandGEM

High Canadian waste disposal rates necessitate landfill gas monitoring and accurate forecasting. CO₂ estimates in LandGEM version 3.02 currently rest on the assumptions that CO₂ is a function of CH₄, where the two gases make up nearly 100% of landfill gas content, leading to overestimated CO₂ collection estimates. A total of 25 cases (five formulas, five approaches) compared annual CO₂ collection at four western Canadian landfills. Despite common use in literature, the 1:1 ratio of CH₄ to CO₂ was not recommended to forecast landfill gas collection in cold climates. The existing modelling approach significantly overestimated CO₂ production in three of four sites, resulting in the highest residual sum of squares. Optimization resulted in the most accurate results for all formulas and approaches, which had the greatest reduction in residual sums of squares (RSS) over the default approach (60.1 to 97.7%). The 1.4 Ratio approach for L _o:L _o-CO2 yielded the second most accurate results for CO₂ flow (mean RSS reduction of 50.2% for all sites and subsection models). The annual k-modified LandGEM calculated k’s via two empirical formulas (based on precipitation) and yielded the lowest accuracy in 12 of 20 approaches. Unlike other studies, strong relationships between optimized annual k’s and precipitation were not observed.

     

Fine‐resolution conservation planning with limited climate‐change information

Climate‐change induced uncertainties in future spatial patterns of conservation‐related outcomes make it difficult to implement standard conservation‐planning paradigms. A recent study translates Markowitz's risk‐diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate‐change scenarios for carrying out fine‐resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk‐return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate‐change information and full climate‐change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate‐change forecasts such that the best possible risk‐return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate‐change information could be reduced by 17% relative to other iterative approaches.     

Sources of Fine Particulate Species in Ambient Air over Lake Champlain Basin,VT

Abstract

This study is a part of an ongoing investigation of the types and locations of emission sources that contribute fine particulate air contaminants to Underhill, VT. The air quality monitoring data used for this study are from the Interagency Monitoring of Protected Visual Environments network for the period of 2001–2003 for the Underhill site. The main source-receptor modeling techniques used are the positive matrix factorization (PMF) and potential source contribution function (PSCF). This new study is intended as a comparison to a previous study of the 1988–1995 Underhill data that successfully revealed a total of 11 types of emission sources with significant contributions to this rural site. This new study has identified a total of nine sources: nitrate-rich secondary aerosol, wood smoke, East Coast oil combustion, automobile emission, metal working, soil/dust, sulfur-rich aerosol type I, sulfur-rich aerosol type II, and sea salt/road salt. Furthermore, the mass contributions from the PMF identified sources that correspond with sampling days with either good or poor visibility were analyzed to seek possible correlations. It has been shown that sulfur-rich aerosol type I, nitrate aerosol, and automobile emission are the most important contributors to visibility degradation. Soil/dust and sea salt/road salt also have an added effect.     

Organizational policy and other factors associated with emergency medical technician seat belt use

INTRODUCTION: The purpose of this study was to determine factors associated with seat belt usage among Emergency Medical Technicians (EMTs). METHODS: As part of biennial re-registration paperwork, nationally registered EMTs completed a survey on the safety and health risks facing Emergency Medical Services (EMS) providers. Respondents were asked to describe their seat belt use while in the front seats of an ambulance. They were categorized as "high" in seat belt use if it had been more than a year since they had not worn their seat belt or "low" in seat belt use if they had not worn their seat belt at least once within the past 12 months. A logistic regression model was fit to estimate the association between seat belt use, organizational seat belt policy, type of EMS organization worked for, EMT certification level, and the size of community where EMS work is performed. RESULTS: Of the 41,823 EMTs that re-registered in 2003, surveys were received from 29,575 (70.7%). A significant interaction between organizational seat belt policy and type of EMS organization was found to exist. Participants reporting no organizational seat belt policy had lower odds of seat belt usage when compared to individuals that do have a seat belt policy. Odds Ratios ranged from 0.20 (95% CI 0.10-0.40) for military organizations to 0.59 (95% CI 0.38-0.93) for private EMS organizations. Paramedics and those working in rural areas also had lower odds of seat belt use. CONCLUSION: Several factors were found to be associated with seat belt usage among EMTs while in the front compartment of an ambulance. However, it appears that only one, organizational policy, is a modifiable characteristic.     

Stakeholder engagement and knowledge exchange in environmental research

It is commonly put forward that effective uptake of research in policy or practice must be built upon a foundation of active knowledge exchange and stakeholder engagement during the research. However, what is often lacking is a systematic appreciation of the specific practices of knowledge exchange and their relative merits. The paper reports on a 2009 survey of 21 research projects within the UK Research Councils' Rural Economy and Land Use Programme regarding the involvement and perceived impact of over a thousand stakeholders in the research. The survey reveals that most stakeholders were involved as research subjects or as event participants. Large numbers were also engaged in the research process itself, including involvement in shaping the direction of research. Stakeholder engagement is perceived as bringing significant benefits to the process of knowledge production. A close relationship is found between mechanisms and approaches to knowledge exchange and the spread of benefits for researchers and stakeholders. Mutual benefits are gained from exchange of staff or where stakeholders are members of research advisory groups. Different stakeholder sectors are also associated with different patterns of engagement, which lead to contrasting impact patterns. Any efforts to alter knowledge exchange processes and outcomes must overcome these differing engagement tendencies. Overall, much greater attention should be given to early processes of knowledge exchange and stakeholder engagement within the lifetime of research projects.     

Estimating the extent and structure of trade in horticultural orchids via social media

The wildlife trade is a lucrative industry involving thousands of animal and plant species. The increasing use of the internet for both legal and illegal wildlife trade is well documented, but there is evidence that trade may be emerging on new online technologies such as social media. Using the orchid trade as a case study, we conducted the first systematic survey of wildlife trade on an international social‐media website. We focused on themed forums (groups), where people with similar interests can interact by uploading images or text (posts) that are visible to other group members. We used social‐network analysis to examine the ties between 150 of these orchid‐themed groups to determine the structure of the network. We found 4 communities of closely linked groups based around shared language. Most trade occurred in a community that consisted of English‐speaking and Southeast Asian groups. In addition to the network analysis, we randomly sampled 30 groups from the whole network to assess the prevalence of trade in cultivated and wild plants. Of 55,805 posts recorded over 12 weeks, 8.9% contained plants for sale, and 22–46% of these posts pertained to wild‐collected orchids. Although total numbers of posts about trade were relatively small, the large proportion of posts advertising wild orchids for sale supports calls for better monitoring of social media for trade in wild‐collected plants.     

Mitigating urban sprawl effects: a collaborative tree and shade intervention in Phoenix,Arizona, USA

Communities in Phoenix are confronted with numerous challenges that adversely affect human health and safety, with disproportionate impacts on low-income communities. While some challenges are being addressed at the city level, new alliances at the neighbourhood level are initiating community development programmes and projects. This article reports on an intervention study carried out in collaboration with community representatives, city staff, and non-profit organisations to mitigate adverse effects of urban sprawl in the Sky Harbour Neighbourhood in Phoenix. Participatory research was conducted to design and test a tree and shade intervention. Challenges associated with navigating community desires and broader principles of sustainable development are discussed. The study offers a replicable and adaptable intervention research design aimed at empowering communities to meet urban challenges.     

A statistical model for predicting PM2.5 for the western United States

ABSTRACT

A new statistical model for predicting daily ground level fine scale particulate matter (PM_2.5) concentrations at monitoring sites in the western United States was developed and tested operationally during the 2016 and 2017 wildfire seasons. The model is site-specific, using a multiple linear regression schema that relies on the previous day’s PM_2.5 value, along with fire and smoke related variables from satellite observations. Fire variables include fire radiative power (FRP) and the National Fire Danger Rating System Energy Release Component index. Smoke variables, in addition to ground monitored PM_2.5, include aerosol optical depth (AOD) and smoke plume perimeters from the National Oceanic and Atmospheric Administration’s Hazard Mapping System. The overall statistical model was inspired by a similar system developed for British Columbia (BC) by the BC Center for Disease Control, but it has been heavily modified and adapted to work in the United States. On average, our statistical model was able to explain 78% of the variance in daily ground level PM_2.5. A novel method for implementation of this model as an operational forecast system was also developed and was tested and used during the 2016 and 2017 wildfire seasons. This method focused on producing a continuously-updating prediction that incorporated the latest information available throughout the day, including both updated remote sensing data and real-time PM_2.5 observations. The diurnal pattern of performance of this model shows that even a few hours of data early in the morning can substantially improve model performance.

Implications: Wildfire smoke events produce significant air quality impacts across the western United States each year impacting millions. We present and evaluate a statistical model for making updating predictions of fine particulate (PM_2.5) levels during smoke events. These predictions run hourly and are being used by smoke incident specialists assigned to wildfire operations, and may be of interest to public health officials, air quality regulators, and the public. Predictions based on this model will be available on the web for the 2019 western U.S. wildfire season this summer.     

An Approach for Evaluating the Repeatability of Rapid Wetland Assessment Methods: The Effects of Training and Experience

We sampled 92 wetlands from four different basins in the United States to quantify observer repeatability in rapid wetland condition assessment using the Delaware Rapid Assessment Protocol (DERAP). In the Inland Bays basin of Delaware, 58 wetland sites were sampled by multiple observers with varying levels of experience (novice to expert) following a thorough training workshop. In the Nanticoke (Delaware/Maryland), Cuyahoga (Ohio), and John Day (Oregon) basins, 34 wetlands were sampled by two expert teams of observers with minimal protocol training. The variance in observer to observer scoring at each site was used to calculate pooled standard deviations (SD_pool), coefficients of variation, and signal-to-noise ratios for each survey. The results showed that the experience level of the observer had little impact on the repeatability of the final rapid assessment score. Training, however, had a large impact on observer to observer repeatability. The SD_pool in the Inland Bay survey with training (2.2 points out of a 0–30 score) was about half that observed in the other three basins where observers had minimal training (SD_pool = 4.2 points). Using the results from the survey with training, we would expect that two sites assessed by different, trained observers who obtain DERAP scores differing by more than 4 points are highly likely to differ in ecological condition, and that sites with scores that differ by 2 or fewer points are within variability that can be attributed to observer differences.