Environmental policies in Europe have successfully eliminated the most visible and immediate harmful effects of air pollution in the last decades. However, there is ample and robust scientific evidence that even at present rates Europe's emissions to the atmosphere pose a significant threat to human health, ecosystems and the global climate, though in a less visible and immediate way. As many of the 'low hanging fruits' have been harvested by now, further action will place higher demands on economic resources, especially at a time when resources are strained by an economic crisis. In addition, interactions and interdependencies of the various measures could even lead to counter-productive outcomes of strategies if they are ignored. Integrated assessment models, such as the GAINS (Greenhouse gas - Air pollution Interactions and Synergies) model, have been developed to identify portfolios of measures that improve air quality and reduce greenhouse gas emissions at least cost. Such models bring together scientific knowledge and quality-controlled data on future socio-economic driving forces of emissions, on the technical and economic features of the available emission control options, on the chemical transformation and dispersion of pollutants in the atmosphere, and the resulting impacts on human health and the environment. The GAINS model and its predecessor have been used to inform the key negotiations on air pollution control agreements in Europe during the last two decades. This paper describes the methodological approach of the GAINS model and its components. It presents a recent policy analysis that explores the likely future development of emissions and air quality in Europe in the absence of further policy measures, and assesses the potential and costs for further environmental improvements. To inform the forthcoming negotiations on the revision of the Gothenburg Protocol of the Convention on Long-range Transboundary Air Pollution, the paper discusses the implications of alternative formulations of environmental policy targets on a cost-effective allocation of further mitigation measures.

Cost-effective control of air quality and greenhouse gases in Europe: Modeling and policy applications

Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts, diversity of stakeholders, and integration of social, economic, and environmental considerations. IEM provides a science-based structure to develop and organize relevant knowledge and information and apply it to explain, explore, and predict the behavior of environmental systems in response to human and natural sources of stress. During the past several years a number of workshops were held that brought IEM practitioners together to share experiences and discuss future needs and directions. In this paper we organize and present the results of these discussions. IEM is presented as a landscape containing four interdependent elements: applications, science, technology, and community. The elements are described from the perspective of their role in the landscape, current practices, and challenges that must be addressed. Workshop participants envision a global scale IEM community that leverages modern technologies to streamline the movement of science-based knowledge from its sources in research, through its organization into databases and models, to its integration and application for problem solving purposes. Achieving this vision will require that the global community of IEM stakeholders transcend social, and organizational boundaries and pursue greater levels of collaboration. Among the highest priorities for community action are the development of standards for publishing IEM data and models in forms suitable for automated discovery, access, and integration; education of the next generation of environmental stakeholders, with a focus on transdisciplinary research, development, and decision making; and providing a web-based platform for community interactions (e.g., continuous virtual workshops).

/pdf/integrated-environmental-modeling-a-vision-and-roadmap-for-1nvakawpfk.pdf

Integrated environmental modeling: A vision and roadmap for the future

Integrated assessment and its inherent platform, integrated modelling, present an opportunity to synthesize diverse knowledge, data, methods and perspectives into an overarching framework to address complex environmental problems. However to be successful for assessment or decision making purposes, all salient dimensions of integrated modelling must be addressed with respect to its purpose and context. The key dimensions include: issues of concern; management options and governance arrangements; stakeholders; natural systems; human systems; spatial scales; temporal scales; disciplines; methods, models, tools and data; and sources and types of uncertainty. This paper aims to shed light on these ten dimensions, and how integration of the dimensions fits in the four main phases in the integrated assessment process: scoping, problem framing and formulation, assessing options, and communicating findings. We provide examples of participatory processes and modelling tools that can be used to achieve integration. This is an overview on integrated assessment and modelling (IAM) for environmental problems.We examine the ten key dimensions of integration in IAM including what is being integrated, why and how.We discuss how the integration dimensions fit into the IAM process.

/pdf/integrated-assessment-and-modelling-3u0m15ggfj.pdf

Integrated assessment and modelling

Scale changes and model linking methods for integrated assessment of agri-environmental systems

A methodology for enhanced flexibility of integrated assessment in agriculture

Integrated Assessment and Modelling (IAM) provides an interdisciplinary approach to support ex-ante decision-making by combining quantitative models representing different systems and scales into a framework for integrated assessment. Scenarios in IAM are developed in the interaction between scientists and stakeholders to explore possible pathways of future development. As IAM typically combines models from different disciplines, there is a clear need for a consistent definition and implementation of scenarios across models, policy problems and scales. This paper presents such a unified conceptualization for scenario and assessment projects. We demonstrate the use of common ontologies in building this unified conceptualization, e.g. a common ontology on assessment projects and scenarios. The common ontology and the process of ontology engineering are used in a case study, which refers to the development of SEAMLESS-IF, an integrated modelling framework to assess agricultural and environmental policy options as to their contribution to sustainable development. The presented common ontology on assessment projects and scenarios can be reused by IAM consortia and if required, adapted by using the process of ontology engineering as proposed in this paper.

J. Alkan-Olsson

Papers

Defining assessment projects and scenarios for policy support: Use of ontology in Integrated Assessment and Modelling

How to manage models outputs aggregation for indicator quantification within SEAMLESS integrated framework