Elite cues,media coverage,and public concern: an integrated path analysis of public opinion on climate change, 2001–2013

To analyze the factors affecting US public concern about the threat of climate change between January 2002 and December 2013, data from 74 separate surveys are used to construct quarterly measures of public concern over global climate change. Five factors should account for changes in levels of concern: extreme weather events, public access to accurate scientific information, media coverage, elite cues, and movement/countermovement advocacy. Structural equation modeling indicates that elite cues, movement advocacy efforts, weather, and structural economic factors influence the level of public concern about climate change. While media coverage exerts an important influence, it is itself largely a function of elite cues and economic factors. Promulgation to the public of scientific information on climate change has no effect. Information-based science advocacy has had only a minor effect on public concern, while political mobilization by elites and advocacy groups is critical in influencing climate change concern.     

A new sampler for stratified lagoon chemical and microbiological assessments

A sampler was needed for a spatial and temporal study of microbial and chemical stratification in a large swine manure lagoon that was known to contain zoonotic bacteria. Conventional samplers were limited to collections of surface water samples near the bank or required a manned boat. A new sampler was developed to allow simultaneous collection of multiple samples at different depths, up to 2.3 m, without a manned boat. The sampler was tethered for stability, used remote control (RC) for sample collection, and accommodated rapid replacement of sterile tubing modules and sample containers. The sampler comprised a PVC pontoon with acrylic deck and watertight enclosures, for a 12 VDC gearmotor, to operate the collection module, and vacuum system, to draw samples into reusable autoclavable tubing and 250-mL bottles. Although designed primarily for water samples, the sampler was easily modified to collect sludge. The sampler held a stable position during deployment, created minimal disturbance in the water column, and was readily cleaned and sanitized for transport. The sampler was field tested initially in a shallow fresh water lake and subsequently in a swine manure treatment lagoon. Analyses of water samples from the lagoon tests showed that chemical and bacterial levels, pH, and EC did not differ between 0.04, 0.47, and 1.0 m depths, but some chemical and bacterial levels differed between winter and spring collections. These results demonstrated the utility of the sampler and suggested that future manure lagoon studies employ fewer or different depths and more sampling dates.     

A graphical assessment and spatial clustering of the Deepwater Horizon oil spill impact on Laughing Gulls

The Deepwater Horizon oil spill occurred in the Gulf of Mexico on April 20, 2010. Considered the largest accidental marine oil spill in history, oil flowed for three months and approximately five million barrels of oil spilled through by mid-July 2010. In this article, we analyze bird data to assess the impact of the oil spill on the Gulf wildlife. Particularly, we want to determine in which regions Laughing Gulls were mostly affected by the oil spill, and whether those regions spatially shifted throughout the year 2010. Though our data sets have some limitations to apply statistical analysis methods, we obtained very interesting results. Our analyses showed the general consistency of the results based on two population data sets (from the 2011 Data Expo and from the eBird community) and justified the use of both publicly available data sets. We showed that the closer the surface oil spill area approached to the Laughing Gulls habitats, the more significant clusters of bird cases were observed.     

Fucus spiralis as monitoring tool of metal contamination in the northwest coast of Portugal under the European Water Framework Directives

Metals (Cd, Cr, Cu, Fe, Mn and Zn) in coastal seawaters and soft tissues of macroalga Fucus spiralis from the northwest coast of Portugal were determined to assess spatial variations of metal bioavailabilities and bioaccumulation factors to compare different ecological quality classifications. Both coastal seawaters and soft tissues of F. spiralis showed significant spatial variations in their metal concentrations along the coast. The macroalgae F. spiralis accumulated more efficiently Cd, Mn and Zn and showed low bioaccumulation factors to Cr, Cu and Fe. Regarding the metal guidelines of the Norwegian Pollution Control Authority, the entire northwest (NW) coast of Portugal in April 2013 should be classified as ‘class I—unpolluted’ for all metals, except in Ave for Cu (‘class II—moderately polluted’) and Cavado for Cd and Cu (‘class II—moderately polluted’), revealing the low metal bioavailabilities of these seawaters. As there were always significant positive correlations between all metals in seawaters and F. spiralis, this macroalga species was considered a suitable monitoring tool of metal contamination in the NW coast of Portugal and a useful aquatic organism to be included in the European Environmental Specimen Banks in order to establish a real-time environmental monitoring network under the European Water Framework Directives.     

Analysis of Key Features of Non-Linear Behaviour Using Recurrence Quantification. Case Study: Urban Airborne Pollution at Mexico City

The use of recurrence plots have been extensively used in various fields. In this work, recurrence plots investigate the changes in the non-linear behaviour of urban air pollution using large datasets of raw data (hourly). This analysis has not been used before to extract information from large datasets for this type of non-linear problem. Two different approaches have been used to tackle this problem. The first approach is to show results according to monitoring network. The second approach is to show the results by particle type. This analysis shows the feasibility of using recurrence analysis for pollution monitoring and control.     

Development of a new risk-based framework to guide investment in water quality monitoring

An innovative framework for optimising investments in water quality monitoring has been developed for use by water and environmental agencies. By utilising historical data, investigating the accuracy of monitoring methods and considering the risk tolerance of the management agency, this new methodology calculates optimum water quality monitoring frequencies for individual water bodies. Such information can be applied to water quality constituents of concern in both engineered and natural water bodies and will guide the investment of monitoring resources. Here we present both the development of the framework itself and a proof of concept by applying it to the occurrence of hazardous cyanobacterial blooms in freshwater lakes. This application to existing data demonstrates the robustness of the approach and the capacity of the framework to optimise the allocation of both monitoring and mitigation resources. When applied to cyanobacterial blooms in the Swan Coastal Plain of Western Australia, we determined that optimising the monitoring regime at individual lakes could greatly alter the overall monitoring schedule for the region, rendering it more risk averse without increasing the amount of monitoring resources required. For water resources with high-density temporal data related to constituents of concern, a similar reduction in risk may be observed by applying the framework.     

A Multiple Criteria Decision Analysis Model Based on ELECTRE TRI-C for Erosion Risk Assessment in Agricultural Areas

This paper deals with a real-world decision-aiding problem for zoning the risk of erosion, total suspended solids emissions, and ecological consequences of their transfers towards the streams. One of these consequences is the decrease of fishes into the streams in agricultural watersheds, because of the clogging of spawning areas. Given the multiple criteria nature of the problem, the originality of our research is to adapt a new decision-aiding sorting method, ELECTRE TRI-C, for identifying risk zones in rural areas, where measures must be taken. The developed model was applied in a small watershed (Low Normandy, France) where the objective was to assess the most appropriate intervention for protecting the reproduction habitat of the salmonid fishes. Agricultural parcels were evaluated on multiple criteria for grouping them into four risk categories, which are related to risk levels as well as priorities on the improvement works. The decision-aiding sorting model is co-constructed, within a constructive approach, through an interaction process between decision-aiding analysts, environmental experts, and local actors for improving transparency and communication on the results. This model is linked with a geographical information system (GIS) for assessing a set of criteria and the visualization of the farming parcels along with their type of intervention they should be submitted to best practices. The assignment results were validated by the environmental experts. These results have a strong impact on the agricultural practices of the farmers into the watersheds. The model proposed in this paper can be considered as a useful decision aid tool in any regions for implementing public agricultural and environmental policies for protecting the ecological areas.     

Evaluating soil quality under a long-term integrated tillage–water–nutrient experiment with intensive rice–wheat rotation in a semi-arid Inceptisol,India

Long-term sustainability and a declining trend in productivity of rice–wheat rotation in the Indo-Gangetic plain, often direct towards the changes in soil quality parameters. Soil quality is decided through few sensitive soil physical, chemical and biological indicators as it cannot be measured directly. The present investigation was carried out to develop a valid soil quality index through some chosen indicators under long-term influences of tillage, water and nutrient-management practices in a rice–wheat cropping system. The experiment consisted of two tillage treatments, three irrigation treatments, and nine nutrient management treatments for both rice and wheat, was continued for 8 years. The index was developed using expert-opinion based conceptual framework model. After harvest of rice, the CFSQI-P (productivity) was higher under puddled situation, whereas CFSQI-EP (environmental protection) was more under non-puddled condition and 3-days of drainage was found promising for all the indices. No-tillage practice always showed higher soil quality index. The treatments either receiving full organics (100 % N) or 25 % substitution of fertilizer N with organics showed higher soil quality indices. Puddling, irrigation after 3 days of drainage and substitution of 25 % recommended fertilizer N dose with FYM in rice could be practiced for maintaining or enhancing soil quality. No-tillage, two irrigations, and domestic sewage sludge in wheat can safely be recommended for achieving higher soil quality.     

Suitability of passive sampling for the monitoring of pharmaceuticals in Finnish surface waters

The occurrence of five pharmaceuticals, consisting of four anti-inflammatory and one antiepileptic drug, was studied by passive sampling and grab sampling in northern Lake Päijänne and River Vantaa. The passive sampling was performed by using Chemcatcher® sampler with a SDB-RPS Empore disk as a receiving phase. In Lake Päijänne, the sampling was conducted during summer 2013 at four locations near the discharge point of a wastewater treatment plant and in the years 2013 and 2015 at four locations along River Vantaa. The samples were analyzed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) in the multiple reaction monitoring mode. The concentrations of carbamazepine, diclofenac, ibuprofen, ketoprofen, and naproxen in Lake Päijänne determined by passive sampling ranged between 1.4–2.9 ng L^?1, 15–35 ng L^?1, 13–31 ng L^?1, 16–27 ng L^?1, and 3.3–32 ng L^?1, respectively. Similarly, the results in River Vantaa ranged between 1.2–40 ng L^?1, 15–65 ng L^?1, 13–33 ng L^?1, 16–31 ng L^?1, and 3.3–6.4 ng L^?1. The results suggest that the Chemcatcher passive samplers are suitable for detecting pharmaceuticals in lake and river waters.