Analysing environmental opinion using highly customisable visualisation tools to understand citizens' attitudes and barriers.

Knowledge of public opinion is key to understanding citizens' attitudes towards environmental policies. However, large polls and surveys generate complex datasets from which it is not always easy to draw conclusions. In addition, tailor-made solutions for analysing public opinion face the challenge of handling too many layers of information, which can easily lead to an overwhelming user experience and impair decision-making. Service design methodologies can support the design of ad hoc visualisation tools focused on user needs. We present Op-e-nion, a case study of a visualisation tool for the analysis of public opinion regarding environmental issues, aimed at administrations and public institutions. The involvement of experts from different fields allowed for the identification of the main metrics necessary to target the least engaged socio-demographic groups as well as the barriers that limited their environmental actions. Experts also highlighted useful aspects of the design process and the final prototype to help them define more effective campaigns and policies to address social challenges and promote citizen action. An innovative step was introduced in the methodology by involving non-state actors in the evaluation of the tool, ensuring problem detection and enhancing the sustainability of the final product. Important aspects for the visualisation of multi-categorical data included simplifying the interaction with the tool while prioritising relevant information, and using highly customizable visualisations to answer specific user requirements and changing needs (i.e. analytical vs. managerial tasks). Improved visualisations of public opinion data will, in turn, better support the development of policies shaped by citizens' concerns.

Decision-support tools to build climate resilience against emerging infectious diseases in Europe and beyond.

Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of infectious diseases in Europe. We propose a framework for the co-production of policy-relevant indicators and decision-support tools that track past, present, and future climate-induced disease risks across hazard, exposure, and vulnerability domains at the animal, human, and environmental interface. This entails the co-development of early warning and response systems and tools to assess the costs and benefits of climate change adaptation and mitigation measures across sectors, to increase health system resilience at regional and local levels and reveal novel policy entry points and opportunities. Our approach involves multi-level engagement, innovative methodologies, and novel data streams. We take advantage of intelligence generated locally and empirically to quantify effects in areas experiencing rapid urban transformation and heterogeneous climate-induced disease threats. Our goal is to reduce the knowledge-to-action gap by developing an integrated One Health-Climate Risk framework.

Assembling the climate story: use of storyline approaches in climate-related science.

Storylines are introduced in climate science to provide unity of discourse, integrate the physical and socioeconomic components of phenomena, and make climate evolution more tangible. The use of this concept by multiple scholar communities and the novelty of some of its applications renders the concept ambiguous nonetheless, because the term hides behind a wide range of purposes, understandings, and methodologies. This semi-systematic literature review identifies three approaches that use storylines as a keystone concept: scenarios-familiar for their use in IPCC reports-discourse-analytical approaches, and physical climate storylines. After screening peer-reviewed articles that mention climate and storylines, 270 articles are selected, with 158, 55, and 57 in each category. The results indicate that each scholarly community works with a finite and different set of methods and diverging understandings. Moreover, these approaches have received criticism in their assembly of storylines: either for lacking explicitness or for the homogeneity of expertise involved. This article proposes that cross-pollination among the approaches can improve the usefulness and usability of climate-related storylines. Among good practices are the involvement of a broader range of scientific disciplines and expertise, use of mixed-methods, assessment of storylines against a wider set of quality criteria, and targeted stakeholder participation in key stages of the process.

How decadal predictions entered the climate services arena: an example from the agriculture sector.

Predicting the variations in climate for the coming 1-10 years is of great interest for decision makers, as this time horizon coincides with the strategic planning of stakeholders from climate-vulnerable sectors such as agriculture. This study attempts to illustrate the potential value of decadal predictions in the development of climate services by establishing interactions and collaboration with stakeholders concerned with food production and security. Building on our experience from interacting with users and the increased understanding of their needs gathered over the years through our participation in various European activities and initiatives, we developed a decadal forecast product that provides tailored and user-friendly information about multi-year dry conditions for the coming five years over global wheat harvesting regions. This study revealed that the coproduction approach, where the interaction between the user and climate service provider is established at an early stage of forecast product development, is a fundamental step to successfully provide useful and ultimately actionable information to the interested stakeholders. The study also provides insights that shed light on the reasons for the delayed entry of decadal predictions in the climate services discourse and practice, obtained from surveying climate scientists and discussing with decadal prediction experts. Finally, it shows the key challenges that this new source of climate information still faces.

Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models.

The application of the multivariate curve resolution method to the analysis of temporal and spatial data variability of hourly measured O3 and NO2 concentrations at nineteen air quality monitoring stations across Catalonia, Spain, during 2015 is shown. Data analyzed included ground-based experimental measurements and predicted concentrations by the CALIOPE air quality modelling system at three horizontal resolutions (Europe at 12 × 12 km2, Iberian Peninsula at 4 × 4 km2 and Catalonia at 1 × 1 km2). Results obtained in the analysis of these different data sets allowed a better understanding of O3 and NO2 concentration changes as a sum of a small number of different contributions related to daily sunlight radiation, seasonal dynamics, traffic emission patterns, and local station environments (urban, suburban and rural). The evaluation of O3 and NO2 concentrations predicted by the CALIOPE system revealed some differences among data sets at different spatial resolutions. NO2 predictions, showed in general a better performance than O3 predictions for the three model resolutions, specially at urban stations. Our results confirmed that the application of the trilinearity constraint during the multivariate curve resolution factor analysis decomposition of the analyzed data sets is a useful tool to facilitate the understanding of the resolved variability sources.

Model development for the assessment of terrestrial and aquatic habitat quality in conservation planning.

There is a growing pressure of human activities on natural habitats, which leads to biodiversity losses. To mitigate the impact of human activities, environmental policies are developed and implemented, but their effects are commonly not well understood because of the lack of tools to predict the effects of conservation policies on habitat quality and/or diversity. We present a straightforward model for the simultaneous assessment of terrestrial and aquatic habitat quality in river basins as a function of land use and anthropogenic threats to habitat that could be applied under different management scenarios to help understand the trade-offs of conservation actions. We modify the InVEST model for the assessment of terrestrial habitat quality and extend it to freshwater habitats. We assess the reliability of the model in a severely impaired basin by comparing modeled results to observed terrestrial and aquatic biodiversity data. Estimated habitat quality is significantly correlated with observed terrestrial vascular plant richness (R(2)=0.76) and diversity of aquatic macroinvertebrates (R(2)=0.34), as well as with ecosystem functions such as in-stream phosphorus retention (R(2)=0.45). After that, we analyze different scenarios to assess the suitability of the model to inform changes in habitat quality under different conservation strategies. We believe that the developed model can be useful to assess potential levels of biodiversity, and to support conservation planning given its capacity to forecast the effects of management actions in river basins.

Analysis of the uncertainty in the monetary valuation of ecosystem services--A case study at the river basin scale.

Ecosystem services provide multiple benefits to human wellbeing and are increasingly considered by policy-makers in environmental management. However, the uncertainty related with the monetary valuation of these benefits is not yet adequately defined or integrated by policy-makers. Given this background, our aim was to quantify different sources of uncertainty when performing monetary valuation of ecosystem services, in order to provide a series of guidelines to reduce them. With an example of 4 ecosystem services (i.e., water provisioning, waste treatment, erosion protection, and habitat for species) provided at the river basin scale, we quantified the uncertainty associated with the following sources: (1) the number of services considered, (2) the number of benefits considered for each service, (3) the valuation metrics (i.e. valuation methods) used to value benefits, and (4) the uncertainty of the parameters included in the valuation metrics. Results indicate that the highest uncertainty was caused by the number of services considered, as well as by the number of benefits considered for each service, whereas the parametric uncertainty was similar to the one related to the selection of valuation metric, thus suggesting that the parametric uncertainty, which is the only uncertainty type commonly considered, was less critical than the structural uncertainty, which is in turn mainly dependent on the decision-making context. Given the uncertainty associated to the valuation structure, special attention should be given to the selection of services, benefits and metrics according to a given context.

Ecosystem services in Mediterranean river basin: climate change impact on water provisioning and erosion control.

The Mediterranean basin is considered one of the most vulnerable regions of the world to climate change and such changes impact the capacity of ecosystems to provide goods and services to human society. The predicted future scenarios for this region present an increased frequency of floods and extended droughts, especially at the Iberian Peninsula. This paper evaluates the impacts of climate change on the water provisioning and erosion control services in the densely populated Mediterranean Llobregat river basin of. The assessment of ecosystem services and their mapping at the basin scale identify the current pressures on the river basin including the source area in the Pyrenees Mountains. Drinking water provisioning is expected to decrease between 3 and 49%, while total hydropower production will decrease between 5 and 43%. Erosion control will be reduced by up to 23%, indicating that costs for dredging the reservoirs as well as for treating drinking water will also increase. Based on these data, the concept for an appropriate quantification and related spatial visualization of ecosystem service is elaborated and discussed.

Sensitivity analysis of ecosystem service valuation in a Mediterranean watershed.

The services of natural ecosystems are clearly very important to our societies. In the last years, efforts to conserve and value ecosystem services have been fomented. By way of illustration, the Natural Capital Project integrates ecosystem services into everyday decision making around the world. This project has developed InVEST (a system for Integrated Valuation of Ecosystem Services and Tradeoffs). The InVEST model is a spatially integrated modelling tool that allows us to predict changes in ecosystem services, biodiversity conservation and commodity production levels. Here, InVEST model is applied to a stakeholder-defined scenario of land-use/land-cover change in a Mediterranean region basin (the Llobregat basin, Catalonia, Spain). Of all InVEST modules and sub-modules, only the behaviour of the water provisioning one is investigated in this article. The main novel aspect of this work is the sensitivity analysis (SA) carried out to the InVEST model in order to determine the variability of the model response when the values of three of its main coefficients: Z (seasonal precipitation distribution), prec (annual precipitation) and eto (annual evapotranspiration), change. The SA technique used here is a One-At-a-Time (OAT) screening method known as Morris method, applied over each one of the one hundred and fifty four sub-watersheds in which the Llobregat River basin is divided. As a result, this method provides three sensitivity indices for each one of the sub-watersheds under consideration, which are mapped to study how they are spatially distributed. From their analysis, the study shows that, in the case under consideration and between the limits considered for each factor, the effect of the Z coefficient on the model response is negligible, while the other two need to be accurately determined in order to obtain precise output variables. The results of this study will be applicable to the others watersheds assessed in the Consolider Scarce Project.

Multivariate curve resolution of organic pollution patterns in the Ebro River surface water-groundwater-sediment-soil system.

Multivariate curve resolution alternating least squares (MCR-ALS) is shown to be a powerful chemometric method for the analysis of environmental monitoring data sets. It allows for the investigation, resolution, identification, and description of pollution patterns distributed over a particular geographical area, time and environmental compartment. An integrated interpretation of the main features characterizing pollution patterns of organic contaminants affecting the Ebro River basin (Catalonia, NE Spain) is attempted using the results obtained by MCR-ALS analysis of surface water, groundwater, sediment and soil data sets obtained in a 3-year extensive monitoring study. Agricultural practices were identified as the main source of surface and groundwater diffuse pollution, while sediments and soils appeared mostly polluted by a contamination pattern mainly loaded by polycyclic aromatic hydrocarbons (PAHs) of possible pyrolitic origin. Additionally, a third pollution pattern related to past and ongoing industrial activities was detected to be principally stored in the sediment compartment. Geographical and temporal distributions of these pollution sources are given.

Quality assessment of the multivariate curve resolution alternating least squares method for the investigation of environmental pollution patterns in surface water.

Multivariate curve resolution alternating least squares is shown to be a powerful chemometric tool for investigation of main surface water contamination patterns affecting a particular geographical area over a period of time. When environmental monitoring data tables are analyzed using this method, the identification of the main contamination patterns, and the description of their geographical and temporal distribution profiles, can be obtained. To show the potential of the proposed method, the investigation of the pesticide contamination affecting the Ebro River delta (Catalonia, NE Spain) during the rice-growing season in 2005, is selected as a case study in this work. Three different contamination patterns of pesticides with different spatial end temporal behaviors were identified. A method validation using simulated data is then proposed to evaluate the suitability of the proposed multivariate curve resolution method for the analysis of the different possible date structures currently occurring in environmental monitoring studies. In particular, different data structures previously encountered in the experimental study of the Ebro River have been investigated in detail. The importance of using either raw or scaled data is contrasted using the simulated data sets. Possible propagation of noise on resolved profiles is also investigated to establish the difference between its effects and the possible ambiguities inherent to multivariate curve resolution methods.

Use of chemometric and geostatistical methods to evaluate pesticide pollution in the irrigation and drainage channels of the Ebro river delta during the rice-growing season.

Data sets obtained from quantitative analysis of seventeen pesticides in water samples from a network of irrigation and drainage channels in the Ebro river delta (Catalonia, NE Spain) have been analysed by chemometric and geostatistical methods. Samples were taken at fourteen locations during the main rice-growing season, from May to August 2005. Principal-component analysis enabled investigation of the spatial and temporal distribution of the main pollution patterns caused by application of pesticides in the region under study. A first pesticide-contamination pattern from the Ebro river was differentiated from a second more specific pattern from the water-drainage channels of the delta, collected from the rice fields. The seasonal peak in this more specific rice pesticide source was observed in July. Coupling the results from chemometric data analysis with use of geostatistical methods was shown to be a useful procedure for discovery of the most significant spatial and monthly variations of the main pesticide-contamination patterns, taking into account the particular geographical structure of the area under study.

Identification and distribution of contamination sources in the Ebro river basin by chemometrics modelling coupled to geographical information systems.

Identification of the main contamination sources of heavy metals, organic compounds and other physicochemical parameters in Ebro river surface waters and description of their temporal and spatial distributions, are analyzed using chemometrics and geostatistical methods. Historical data available from the Confederación Hidrográfica del Ebro (CHE), which is the organization in charge of the management of the Ebro river basin; covering different years since 1992 for water, sediments and fish samples are investigated. Due to the great amount of data in these databases and to their complexity, chemometrics modelling (using principal components analysis, PCA) coupled to geographical information systems (GIS) is proposed to evaluate the environmental quality of the Ebro river basin.