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The determinants of farmers' decisions to reduce greenhouse gas (GHG) emissions are currently not well understood. This study takes several new angles in investigating farmers' climate change mitigation behaviour. Based on two identical surveys among representative samples of Dutch farmers, this study examines the underlying determinants and motivating factors for three different types of climate change mitigation measures on farms: energy saving, the production of renewable energy and reduction of emissions of methane and nitrous oxide (non-CO 2 emissions). Furthermore, the study explores whether farmers' awareness and behaviour has been influenced by a communication campaign carried out by the government of the Netherlands between 2012 and 2015. Four major conclusions emerge. Firstly, the analyses demonstrate that accounting for the cost-effectiveness and technology readiness level (TRL) of different types of climate change mitigation measures provides for a better understanding of the factors that motivate farmers to adopt these measures. Secondly, neither the willingness to take GHG reduction measures nor knowledge on GHG emissions are consistent motivating factors for energy-related measures. Thirdly, it seems that external factors, such as economic hardship, dominate the overall environmental awareness of farmers. Fourthly, the farmer's propensity to innovate proved to be the strongest and most consistent predictor of both the willingness and the actual adoption of climate change mitigation technologies. Therefore, focusing on making farmers more open to change and general innovation in campaigns in the agricultural sector might be more effective than campaigns focusing specifically on climate change mitigation.

Since the European Energy Efficiency Directive, a lot of attention has been paid to energy saving measures, including how to overcome the barriers for implementation. This paper addresses the dilemmas of the Dutch dairy sector, where farms are getting bigger and mechanization is increasing, while at the same time the sector is aiming for improved energy efficiency and sustainability. With an online tool which systematically recorded the energy performance of dairy farmers, a unique dataset on farm energy use with more than 25,000 observations over the years 2015–2018 was obtained. This allows for a robust analysis of the determinants of energy efficiency in the sector, using panel data analyses. The results of this study reveal three major trends. First, the on-farm use of solar panels proves to be the most significant determinant for reducing non-renewable energy use. Second, gains in energy efficiency triggered by government policies are countervailed by the continuous trend of mechanization, with especially automatic milking systems causing lower energy efficiency. Third, the increasing economies of scale in milk production substantially improve per-unit energy efficiency. However, the increased need for mechanization related to higher on-farm production can cancel out this economies-of-scale effect. These findings add important new insights to the literature on cleaner production in farms and have important policy implications. Strategies for more energy-efficient farming should entail two directions for innovation: first, the stimulation of more energy efficient automatic milking systems, and second, the stimulation of solar energy production on farms including a better on-farm utilization of solar electricity.

Since the European Energy Efficiency Directive, a lot of attention has been paid to energy saving measures, including how to overcome the barriers for implementation. This paper addresses the dilemmas of the Dutch dairy sector, where farms are getting bigger and mechanization is increasing, while at the same time the sector is aiming for improved energy efficiency and sustainability. With an online tool which systematically recorded the energy performance of dairy farmers, a unique dataset on farm energy use with more than 25,000 observations over the years 2015–2018 was obtained. This allows for a robust analysis of the determinants of energy efficiency in the sector, using panel data analyses. The results of this study reveal three major trends. First, the on-farm use of solar panels proves to be the most significant determinant for reducing non-renewable energy use. Second, gains in energy efficiency triggered by government policies are countervailed by the continuous trend of mechanization, with especially automatic milking systems causing lower energy efficiency. Third, the increasing economies of scale in milk production substantially improve per-unit energy efficiency. However, the increased need for mechanization related to higher on-farm production can cancel out this economies-of-scale effect. These findings add important new insights to the literature on cleaner production in farms and have important policy implications. Strategies for more energy-efficient farming should entail two directions for innovation: first, the stimulation of more energy efficient automatic milking systems, and second, the stimulation of solar energy production on farms including a better on-farm utilization of solar electricity.

AbstractFlooding is one of the most significant natural disasters worldwide. Nevertheless, voluntary take‐up of individual damage reduction measures is low. A potential explanation is that flood risk perceptions of individual homeowners are below objective estimates of flood risk, which may imply that they underestimate the flood risk and the damage that can be avoided by damage reduction measures. The aim of this article is to assess possible flood risk misperceptions of floodplain residents in the Netherlands, and to offer insights into factors that are related with under‐ or overestimation of perceived flood risk. We analyzed survey data of 1,848 homeowners in the Dutch river delta and examine how perceptions of flood probability and damage relate to objective risk assessments, such as safety standards of dikes, as well as heuristics, including the availability heuristic and the affect heuristic. Results show that many Dutch floodplain inhabitants significantly overestimate the probability, but underestimate the maximum expected water level of a flood. We further observe that many respondents apply the availability heuristic.