Transition to low-carbon economy: Assessing cumulative impacts of individual behavioral changes

© 2018 The Authors Changing residential energy demand can play an essential role in transitioning to a green economy. Environmental psychology suggests that behavioral changes regarding energy use are affected by knowledge, awareness, motivation and social learning. Data on various behavioral drivers of change can explain energy use at the individual level, but it provides little information about implications for macro energy demand on regional or national levels. We address this challenge by presenting a theoretically-based and empirically-driven agent-based model to track aggregated impacts of behavioral changes among heterogeneous households. We focus on the representation of the multi-step changes in individual energy use behavior and on a quantitative assessment of their aggregated impacts on the regional level. We understand the behavioral complexity of household energy use as a dynamic process unfolding in stages, and explore the barriers for utilizing the full potential of a region for emissions reduction. We suggest a policy mix that facilitates mutual learning among consumers

Exploring the Information Base Needed for Sustainable Management of Rangeland Resources for Improved Livelihoods

Pastoralism is one of the most sustainable production systems worldwide and plays a major role in safeguarding ecosystem services and biodiversity in rangelands. The unique biological and cultural diversity of rangelands contributes to goods, services and knowledge that benefit humans also beyond the herding communities. Yet data currently available on grassland, forestry, agriculture and livestock are inadequate for informing policymaking on rangeland-based livestock systems. A review of global environmental assessments, online databases, peer-reviewed literature and international project documents showed that available information seldom disaggregates rangelands from other ecosystems or pastoralists from other rural dwellers. Few peer-reviewed publications address pastoral and rangeland issues combined. While some international projects present contextualised information on cases of pastoralism and rangelands, most do not share the data on their websites. A challenge encountered when seeking information is the inconsistency in defining pastoralists and rangelands. Estimates of the total number of pastoralists vary from 22 million to over half a billion; estimates of area covered by rangelands vary from 18% to 80% of the world’s land surface. The variation in definitions and lack of disaggregation of data lead to significant knowledge gaps on the condition and trends of pastoralism and rangelands. These therefore tend to be devalued. Underrating benefits of livestock mobility and inaccurate data on rangeland degradation could cause governments to blame and dismantle traditionally sustainable pastoral systems – in other words, ‘fix’ something that’s not broken. Without good data on pastoralists and rangelands, the impacts of current policies on these livelihoods and ecosystems cannot be assessed, and sustainable use and management of rangelands for improved livelihoods may be hindered. Improving the information base is high on the agenda of the initiative for an International Year of Rangelands and Pastoralists to increase global awareness of the importance of rangelands and pastoralists for livelihoods and healthy ecosystems

Demand-side solutions for climate mitigation: Bottom-up drivers of household energy behavior change in the Netherlands and Spain

© 2019 The Authors Households are responsible for 70% of CO2 emissions (directly and indirectly). While households as agents of change increasingly become a crucial element in energy transitions, bottom-up mechanisms facilitating behavioral change are not fully understood. A scientific understanding of individual energy use, requires eliciting factors that trigger or inhibit changes in energy behavior. This paper explores individual energy consumption practices and behavioral aspects that affect them. We quantitatively study the determinants of three energy actions: (1) investments in house insulation, solar panels and/or energy-efficient appliances, (2) conservation of energy by changing energy-use habits like switching off unused devices or adjusting house temperature, and (3) switching to green(er) electricity sources. To address this goal, we conduct a comprehensive survey among households (N = 1790) in two EU regions: Overijssel, the Netherlands and Navarre, Spain. We use probit regression to estimate how behavioral factors, households’ socioeconomic characteristics and structural attributes of dwellings influence energy related actions. Our analysis demonstrates that awareness and personal and social norms are as important as monetary factors. Moreover, education and structural dwelling factors significantly affect households’ actions. These results have implications for governmental policies aimed at reducing residential CO2 footprints and facilitating demand-side solutions in a transition to low-carbon economy

Energizing building renovation: Unraveling the dynamic interplay of building stock evolution, individual behaviour, and social norms

In recent years, discussions surrounding climate change have increasingly emphasized the significance of demand-side solutions. This shift has led to an interdisciplinary and bottom-up approach aimed at supporting global efforts to mitigate climate change. However, conventional modelling tools used to understand the energy demand system and to inform policymaking often fall short in capturing bottom-up dynamics accurately and at the required level of granularity. This is particularly evident in the nuanced and complex aspects of behavioural and social changes and their interactions. This research introduces a novel coupled -agent-based and integrated assessment modelling framework designed to analyse the advantages arising from diversity in renovation decisions, social dynamics, and the evolution of residential building stocks. This study demonstrates that, to effectively formulate realistic policies leading to substantial changes in building energy demand, policymakers require decision-support tools that extend beyond the confines of the rationality principle

Exploring low-carbon futures: A web service approach to linking diverse climate-energy-economy models

© 2019 by the authors. The use of simulation models is essential when exploring transitions to low-carbon futures and climate change mitigation and adaptation policies. There are many models developed to understand socio-environmental processes and interactions, and analyze alternative scenarios, but hardly one single model can serve all the needs. There is much expectation in climate-energy research that constructing new purposeful models out of existing models used as building blocks can meet particular needs of research and policy analysis. Integration of existing models, however, implies sophisticated coordination of inputs and outputs across different scales, definitions, data and software. This paper presents an online integration platform which links various independent models to enhance their scope and functionality. We illustrate the functionality of this web platform using several simulation models developed as standalone tools for analyzing energy, climate and economy dynamics. The models differ in levels of complexity, assumptions, modeling paradigms and programming languages, and operate at different temporal and spatial scales, from individual to global. To illustrate the integration process and the internal details of our integration framework we link an Integrated Assessment Model (GCAM), a Computable General Equilibrium model (EXIOMOD), and an Agent Based Model (BENCH). This toolkit is generic for similar integrated modeling studies. It still requires extensive pre-integration assessment to identify the ‘appropriate’ models and links between them. After that, using the web service approach we can streamline module coupling, enabling interoperability between different systems and providing open access to information for a wider community of users

Assessing the macroeconomic impacts of individual behavioral changes on carbon emissions

© 2019, The Author(s). In the last decade, instigated by the Paris agreement and United Nations Climate Change Conferences (COP22 and COP23), the efforts to limit temperature increase to 1.5 °C above pre-industrial levels are expanding. The required reductions in greenhouse gas emissions imply a massive decarbonization worldwide with much involvement of regions, cities, businesses, and individuals in addition to the commitments at the national levels. Improving end-use efficiency is emphasized in previous IPCC reports (IPCC 2014). Serving as the primary ‘agents of change’ in the transformative process towards green economies, households have a key role in global emission reduction. Individual actions, especially when amplified through social dynamics, shape green energy demand and affect investments in new energy technologies that collectively can curb regional and national emissions. However, most energy-economics models—usually based on equilibrium and optimization assumptions—have a very limited representation of household heterogeneity and treat households as purely rational economic actors. This paper illustrates how computational social science models can complement traditional models by addressing this limitation. We demonstrate the usefulness of behaviorally rich agent-based computational models by simulating various behavioral and climate scenarios for residential electricity demand and compare them with the business as usual (SSP2) scenario. Our results show that residential energy demand is strongly linked to personal and social norms. Empirical evidence from surveys reveals that social norms have an essential role in shaping personal norms. When assessing the cumulative impacts of these behavioral processes, we quantify individual and combined effects of social dynamics and of carbon pricing on individual energy efficiency and on the aggregated regional energy demand and emissions. The intensity of social interactions and learning plays an equally important role for the uptake of green technologies as economic considerations, and therefore in addition to carbon-price policies (top-down approach), implementing policies on education, social and cultural practices can significantly reduce residential carbon emissions