Do investments in phosphorus recovery from dairy processing wastewater pay off?

While phosphorus fertilizers contribute to food security, part of the introduced phosphorus dissipates into water bodies leading to eutrophication. At the same time, conventional mineral phosphorus sources are increasingly scarce. Therefore, closing phosphorus cycles reduces pollution while decreasing trade dependence and increasing food security. A major part of the phosphorus loss occurs during food processing. In this article, we combine a systematic literature review with investment and efficiency analysis to investigate the financial feasibility of recovering phosphorus from dairy processing wastewater. This wastewater is particularly rich in phosphorus, but while recovery technologies are readily available, they are rarely adopted. We calculate the Net Present Value (NPV) of investing in phosphorus recycling technology for a representative European dairy processing company producing 100,000 tonnes of milk per year. We develop sensitivity scenarios and adjust the parameters accordingly. Applying struvite precipitation, the NPV can be positive in two scenarios. First, if the phosphorus price is high (1.51 million EUR) or second if phosphorus recovery is a substitute for mandatory waste disposal (1.48 million EUR). However, for a variety of methodological specifications, the NPV is negative, mainly because of high input costs for chemicals and energy. These trade-offs between off-setting pollution and reducing energy consumption imply, that policy makers and investors should consider the energy source for phosphorus recovery carefully.

Assessing expected utility and profitability to support decision-making for disease control strategies in ornamental heather production.

Many farmers hesitate to adopt new management strategies with actual or perceived risks and uncertainties. Especially in ornamental plant production, farmers often stick to current production strategies to avoid the risk of economically harmful plant losses, even though they may recognize the need to optimize farm management. This work focused on the economically important and little-researched production system of ornamental heather (Calluna vulgaris) to help farmers find appropriate measures to sustainably improve resource use, plant quality, and profitability despite existing risks. Probabilistic cost-benefit analysis was applied to simulate alternative disease monitoring strategies. The outcomes for more intensive visual monitoring, as well as sensor-based monitoring using hyperspectral imaging were simulated. Based on the results of the probabilistic cost-benefit analysis, the expected utility of the alternative strategies was assessed as a function of the farmer's level of risk aversion. The analysis of expected utility indicated that heather production is generally risky. Concerning the alternative strategies, more intensive visual monitoring provides the highest utility for farmers for almost all levels of risk aversion compared to all other strategies. Results of the probabilistic cost-benefit analysis indicated that more intensive visual monitoring increases net benefits in 68% of the simulated cases. The application of sensor-based monitoring leads to negative economic outcomes in 85% of the simulated cases. This research approach is widely applicable to predict the impacts of new management strategies in precision agriculture. The methodology can be used to provide farmers in other data-scarce production systems with concrete recommendations that account for uncertainties and risks. Supplementary information: The online version contains supplementary material available at 10.1007/s11119-022-09909-z.

Extreme heat reduces insecticide use under real field conditions.

Insecticide use and its adverse environmental and health effects are expected to further increase in a warming climate. We here show that farmers' insecticide use, however, declines substantially when facing extreme heat. Using the example of Colorado potato beetles (Leptinotarsa decemlineata) in Switzerland, we find an 11.5% reduction of insecticide use for each day and degree that maximum temperatures exceed 34 °C in the potato growing season. Importantly, our analysis accounts for farmers' behavior under real field conditions, considering the potential adaption of farming practices to extreme heat. It, therefore, highlights how to combine methods to assess and improve our knowledge on the combined major challenges of reducing pesticide risks and coping with the effects of climate change on agriculture while accounting for human behavior. In the analysis, we provide various robustness checks with regard to the definition of temperature extremes, pesticide use indicators, and the chosen statistical model. We further distinguish the principal drivers of the identified effect and find strong evidence that insecticide use reductions are mainly driven by heat-induced decreases in pest pressure rather than heat-induced yield losses that render insecticide applications too expensive. We conclude that similar investigations for other crops and countries are required to assess and understand farmers changing pesticide use decisions under climate change.

Behavioral weather insurance: Applying cumulative prospect theory to agricultural insurance design under narrow framing.

Experience across many countries shows that, without large premium subsidies, crop insurance uptake rates are generally low. In this article, we propose to use the cumulative prospect theory to design weather insurance products for situations in which farmers frame insurance narrowly as a stand-alone investment. To this end, we introduce what we call "behavioral weather insurance" whereby insurance contract parameters are adjusted to correspond more closely with farmers' preferences. Depending on farmers' preferences, we find that a stochastic multiyear premium increases the prospect value of weather insurance, while a zero deductible design does not. We suggest that insurance contracts should be tailored precisely to serve farmers' needs. This offers potential benefits for both the insurer and the insured.

Publisher Correction: The Effects of Extreme Weather on Apple Quality.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The Effects of Extreme Weather on Apple Quality.

A large literature has documented the effects of weather on agricultural yields. However, weather not only impacts the quantity produced, but also the quality of the product. Due to data limitations, the quality effects have primarily been studied using lab experiments for specific attributes, and the financial implications for farmers of a quality effect are less clear. Using a unique longitudinal micro-level data set of Swiss apple orchards that include information on both the quantity produced as well as the quality, we show that the latter can have an even larger effect on farm revenue. Ignoring the quality of the harvested product substantially biases the impact of weather extremes on agricultural income and the potential effects of climate change. Our quality measure is the orchard-year specific price shock. If an orchard gets a lower price for its specific apple variety compared to previous years and compared to other orchards in the same year, we observe the market's valuation of its inferior quality accounting for overall price movements (other orchards growing same variety that year) as well as orchard specific factors (orchard fixed effects). We find that spring frost events induce farm gate price drops and thus revenue reductions of up to 2.05% per hour of exposure.

Phenology Information Contributes to Reduce Temporal Basis Risk in Agricultural Weather Index Insurance.

Weather risks are an essential and increasingly important driver of agricultural income volatility. Agricultural insurances contribute to support farmers to cope with these risks. Among these insurances, weather index insurances (WII) are an innovative tool to cope with climatic risks in agriculture. Using WII, farmers receive an indemnification not based on actual yield reductions but are compensated based on a measured weather index, such as rainfall at a nearby weather station. The discrepancy between experienced losses and actual indemnification, basis risk, is a key challenge. In particular, specifications of WII used so far do not capture critical plant growth phases adequately. Here, we contribute to reduce basis risk by proposing novel procedures how occurrence dates and shifts of growth phases over time and space can be considered and test for their risk reducing potential. Our empirical example addresses drought risks in the critical growth phase around the anthesis stage in winter wheat production in Germany. We find spatially explicit, public and open databases of phenology reports to contribute to reduce basis risk and thus improve the attractiveness of WII. In contrast, we find growth stage modelling based on growing degree days (thermal time) not to result in significant improvements.