Multivariate Condition Assessment of Watersheds with Linked Micromaps

A challenge for statewide stream monitoring is visualizing the spatial and statistical characteristics of such data to compare the biotic condition of watersheds and relate that condition to watershed‐level estimates of instream variables. We used linked micromaps on stream survey data of 25 subbasins (766‐5,982 km²) for biotic condition, nine water quality, and two habitat variables. Subbasin biotic condition was negatively correlated with conductivity, magnesium and sulfate concentrations, and weakly positively correlated with habitat scores of sedimentation and embeddedness, with higher scores indicating better habitat. Positive spatial autocorrelation was detected among the subbasins in both habitat variables, iron concentration, pH, and exceedances of fecal coliform criteria as shown in linked micromaps. A spatial principal components analysis reduced the 11 environmental variables to two principal axes. The first axis synthesized a gradient of water quality and habitat scores among the subbasins. Subbasin biotic condition regressed on first axis subbasin scores had a significant, negative slope and accounted for 55% of the variation. Subbasins in degraded biotic condition had elevated conductivities and ion concentrations in northern and southern subbasins, and low habitat scores in western subbasins. Through linked micromaps, we compared the biotic condition among subbasins and identified stressors prevalent among subbasins that affected biotic condition.     

Sustainable Development by Design: Review of Life Cycle Design and Related Approaches

Abstract

The quality of stationary source emission factors is typically described using data quality ratings, which provide no quantification of the precision of the emission factor for an average source, nor of the variability from one source to another within a category. Variability refers to actual differences caused by differences in feedstock composition, design, maintenance, and operation. Uncertainty refers to lack of knowledge regarding the true emissions. A general methodology for the quantification of variability and uncertainty in emission factors, activity factors, and emission inventories (EIs) is described, featuring the use of bootstrap simulation and related techniques. The methodology is demonstrated via a case study for a selected example of NO_x emissions from coal-fired power plants. A prototype software tool was developed to implement the methodology. The range of interunit variability in selected activity and emission factors was shown to be as much as a factor of 4, and the range of uncertainty in mean emissions is shown to depend on the interunit variability and sample size. The uncertainty in the total inventory of ?16 to +19% was attributed primarily to one technology group, suggesting priorities for collecting data and improving the inventory. The implications for decision-making are discussed.     

Ethnicity and media: a study of English and non-English language print media coverage of water issues in Sydney

ABSTRACT

It is critical to understand how matters relating to water are reported, or ignored, among linguistically diverse media and to understand the possible influence this may have on the conception of water issues among ethnically diverse groups. This research analysed five daily newspapers published in Sydney between 2011 and 2012 in three languages (English, Chinese and Korean) and found that water issues were presented differently by newspapers across language divides in Sydney. These differences may contribute to diverse conceptual constructions of water problems and water management among ethnically diverse communities. After allowing for the influence of other variables, this research highlights the necessity to investigate media construction of water issues in various Non-English language publications as an important approach to improving situated and place-based water awareness in an ethnically diverse city.     

PM10 Concentration Measurements in Dublin City

Mass Concentration of ambient particulate matter with an aerodynamic diameter less than 10µm (PM10) are reported for the first time for a range of sites in Dublin City over a 6 month period from January 1st 1996 to June 30th 1996. PM10 gravimetric mass concentration measurements are made with low flow Partisol 2000 air samplers using an impaction type PM10 inlet and 47mm diameter glass fibre filters. In addition, much finer time resolution measurements (minimum sampling frequency of 30 minutes) are made using a tapered element oscillating microbalance (TEOM) PM10 mass monitor. These PM10 mass concentrations methods are also compared with mass concentration inferred using the standard black smoke method. Analysis of the ambient mass concentration data with reference to traffic density and meteorological influences are presented. Results for the first six months of 1996 show that the average PM10 values range from a high of 49 µg m-3 at the Dublin city centre site to 14 µg m-3 at one of the suburban sites. Intercomparison between PM10 and black smoke mass concentrations show that the relationship is site specific. Statistical analysis between PM10 levels and car traffic number show a positive correlation while a weak negative correlation is found between PM10 levels and rainfall amount, wind speed and air temperature.     

Improving Predictive Models of In‐Stream Phosphorus Concentration Based on Nationally‐Available Spatial Data Coverages

Spatial data are playing an increasingly important role in watershed science and management. Large investments have been made by government agencies to provide nationally‐available spatial databases; however, their relevance and suitability for local watershed applications is largely unscrutinized. We investigated how goodness of fit and predictive accuracy of total phosphorus (TP) concentration models developed from nationally‐available spatial data could be improved by including local watershed‐specific data in the East Fork of the Little Miami River, Ohio, a 1,290 km² watershed. We also determined whether a spatial stream network (SSN) modeling approach improved on multiple linear regression (nonspatial) models. Goodness of fit and predictive accuracy were highest for the SSN model that included local covariates, and lowest for the nonspatial model developed from national data. Septic systems and point source TP loads were significant covariates in the local models. These local data not only improved the models but enabled a more explicit interpretation of the processes affecting TP concentrations than more generic national covariates. The results suggest SSN modeling greatly improves prediction and should be applied when using national covariates. Including local covariates further increases the accuracy of TP predictions throughout the studied watershed; such variables should be included in future national databases, particularly the locations of septic systems.     

Life-cycle assessment of 11 kV electrical overhead lines and underground cables

The life-cycle impacts of five different 11 kV electrical power cables (three overhead lines and two underground cables) were analysed. These were compared by their embodied impacts in production and total lifetime operational impacts. The life-cycle results revealed there to be three key issues, the impacts of climate change, fossil fuel depletion, and particulate matter formation (PMF). The former two were of particular significance. The embodied impacts, which are those associated with the materials, were generally determined to be insignificant. The exception was for underground cables at low operating loads. Under these conditions PMF was more significant as a result of the high embodied impacts of the cables. Further analysis revealed that these impacts could be mitigated with an end of life material recovery program. At present the underground cables are not recovered, but if they were the recycling benefits would give rise to a notable improvement in PMF. For the other impact categories operational conductor losses were the dominant cause of impacts. In summary it was concluded that to minimise the life-cycle impacts of 11 kV cables the system with the lowest conductor resistance should be selected.     

Allowing macroalgae growth forms to emerge: Use of an agent-based model to understand the growth and spread of macroalgae in Florida coral reefs,with emphasis on Halimeda tuna

The growth patterns of macroalgae in three-dimensional space can provide important information regarding the environments in which they live, and insights into changes that may occur when those environments change due to anthropogenic and/or natural causes. To decipher these patterns and their attendant mechanisms and influencing factors, a spatially explicit model has been developed. The model SPREAD (SPatially-explicit Reef Algae Dynamics), which incorporates the key morphogenetic characteristics of clonality and morphological plasticity, is used to investigate the influences of light, temperature, nutrients and disturbance on the growth and spatial occupancy of dominant macroalgae in the Florida Reef Tract. The model species, Halimeda and Dictyota spp., are modular organisms, with an “individual” being made up of repeating structures. These species can also propagate asexually through clonal fragmentation. These traits lead to potentially indefinite growth and plastic morphology that can respond to environmental conditions in various ways. The growth of an individual is modeled as the iteration of discrete macroalgal modules whose dynamics are affected by the light, temperature, and nutrient regimes. Fragmentation is included as a source of asexual reproduction and/or mortality. Model outputs are the same metrics that are obtained in the field, thus allowing for easy comparison. The performance of SPREAD was tested through sensitivity analysis and comparison with independent field data from four study sites in the Florida Reef Tract. Halimeda tuna was selected for initial model comparisons because the relatively untangled growth form permits detailed characterization in the field. Differences in the growth patterns of H. tuna were observed among these reefs. SPREAD was able to closely reproduce these variations, and indicate the potential importance of light and nutrient variations in producing these patterns.     

Evaluation of the best compromise between the urban air quality monitoring resolution by diffusive sampling and resource requirements

The need to collect data representative of overall urban pollution is all-important in order to monitor the population exposure. High spatial resolution monitoring using diffusive samplers allows studying of the urban pollutant distribution, thus enabling deeper investigation of their generation and diffusion mechanisms. Nevertheless, such a monitoring campaign has a certain cost. In this study we point out how to find the best compromise between the number of necessary measurements and the affordable costs for monitoring campaigns. We also describe an innovative method for the proper design of a fixed urban monitoring network by means of preliminary high spatial resolution campaigns using diffusive samplers. Four European capital cities (Dublin, Madrid, Paris and Rome) were monitored six times, each time for seven days. Benzene, toluene, ethylbenzene, xylenes (BTEX) and NO(2) concentrations were measured at 146 sites in Dublin, 293 in Madrid, 339 in Paris and 290 in Rome. Multiscale grids have been drawn which ranged in mesh size from 500 m to 2 km. The statistical processing of data produced a twofold result: the creation of isoconcentration maps with geostatistical procedures, and an algorithm aimed at locating the minimum number of sampling sites where the fixed monitoring stations should be placed. Average urban levels estimated on the basis of these selected sites differ by less than 8% from those calculated on the whole populations of the sampled points. The aim of this work is to investigate how far the resolution of a monitoring campaign of urban pollution by diffusive sampling can be reduced, thus making the monitoring less expensive in terms of human and financial resources, while preserving the same quality of the results that could be achieved with a higher resolution. We found that there is no significant loss of information when the resolution of the monitoring grid for BTEX is lowered to a mesh size of 1.85 km, that is a sampling site each 3.4 km(2), and that the minimum number of sampling sites to be used is N = 0.29 A, where A is the urban surface to be monitored (in km(2)). As the spatial distribution of NO(2) is less sensitive to the distance from the emission source than that of BTEX, this relationship could be retained as a valid lower limit for the mesh grid size also for NO(2) monitoring.     

The influence of atmospheric pressure on landfill methane emissions

Landfills are the largest source of anthropogenic methane (CH4) emissions to the atmosphere in the United States. However, few measurements of whole landfill CH4 emissions have been reported. Here, we present the results of a multi-season study of whole landfill CH4 emissions using atmospheric tracer methods at the Nashua, New Hampshire Municipal landfill in the northeastern United States. The measurement data include 12 individual emission tests, each test consisting of 5-8 plume measurements. Measured emissions were negatively correlated with surface atmospheric pressure and ranged from 7.3 to 26.5 m3 CH4 min(-1). A simple regression model of our results was used to calculate an annual emission rate of 8.4 x 10(6) m3 CH4 year(-1). These data, along with CH4 oxidation estimates based on emitted landfill gas isotopic characteristics and gas collection data, were used to estimate annual CH4 generation at this landfill. A reported gas collection rate of 7.1 x 10(6) m3 CH4 year(-1) and an estimated annual rate of CH4 oxidation by cover soils of 1.2 x 10(6) m3 CH4 year(-1) resulted in a calculated annual CH4 generation rate of 16.7 x 10(6) m3 CH4 year(-1). These results underscore the necessity of understanding a landfill's dynamic environment before assessing long-term emissions potential.