Low-cost sensor technology has been available for several years and has the potential to complement official monitoring networks. The current generation of nitrogen dioxide (NO₂) sensors suffers from various technical problems. This study explores the added value of calibration models based on (multiple) linear regression including cross terms on the performance of an electrochemical NO₂ sensor, the B43F manufactured by Alphasense. Sensor data were collected in duplicate at four reference sites in the Netherlands over a period of one year. It is shown that a calibration, using O₃ and temperature in addition to a reference NO₂ measurement, improves the prediction in terms of R² from less than 0.5 to 0.69–0.84. The uncertainty of the calibrated sensors meets the Data Quality Objective for indicative methods specified by the EU directive in some cases and it was verified that the sensor signal itself remains an important predictor in the multilinear regressions. In practice, these sensors are likely to be calibrated over a period (much) shorter than one year. This study shows the dependence of the quality of the calibrated signal on the choice of these short (monthly) calibration and validation periods. This information will be valuable for determining short-period calibration strategies.

In rural areas, livestock farming is a source of environmental concern. We describe a citizen science (CS) project in Venray, the Netherlands, where air quality was measured at livestock farms and surrounding residential premises. We used low-cost methods to measure air quality components and facilitated a dialogue between stakeholders about the results and solutions for cleaner air. PM_2.5 and PM₁₀ were measured using Nova Fitness SDS011 sensors, nitrogen dioxide (NO₂) and ammonia (NH₃) using Palmes tubes and odour annoyance was reported. Particulate Matter (PM) concentrations were higher close to layer farms, but elevated concentrations were limited at other farms and residential locations. NO₂ concentrations were elevated near busy roads, and higher NH₃ values were measured near livestock farms. Reporting of odour annoyance was limited, yet during the dialogue residents indicated that this was their largest concern. While both farmers and residents agreed with the general conclusions, they still preferred opposing measures. We conclude that characterisation of air quality using low-cost methods is possible, but expert guidance is needed. Moreover, education, commitment of participants and involvement of independent parties are crucial to ensuring a productive dialogue between stakeholders. The insights gained by participants and resulting dialogue were the greatest benefits of this CS approach.

Transitioning towards more plant-based protein diets is essential for public and planetary health. Current research about consumption practices of protein sources provides limited insight in the multidisciplinary nature and interconnectivity of the food environment. This study aimed to collect mental models of review authors by synthesizing both their implicit and explicit system views into an overarching system view. Published reviews were used to select participants and identify variables that explain the protein transition in relation to the food environment. To overcome differences in disciplines and scale levels (e.g. individual, interpersonal, environmental), variables were organized according to the Determinants of Nutrition and Eating Framework. Eight review authors shared their mental models in an interview. Participants were asked to construct a causal loop diagram (CLD), a tool proven valuable in making one's ontology explicit to others. Implicit system views in narrative were converted into CLDs using a coding framework. The overarching system view suggests that a multitude of feedback loops sustain current consumption patterns of protein sources, for example by reinforcement through habit, availability and peer support. Several aspects require further research, such as variable relationships that were subject to disagreement and the lack of reciprocity between the physical and social elements of the food environment. In addition, knowledge gaps were exposed, including long-term behaviour and interaction of multiple variables. As a boundary object, the overarching system view can facilitate the direction of future research. The findings underscore the interconnected nature of many disparate elements within the food environment, stressing the need for holistic methods like systems thinking. These are essential in developing a systemic understanding and facilitating the transition towards more plant-based diets.

A shift to more plant-based diets is crucial for human and planetary health, yet research often overlooks the complexities of the food environment. This study applied system archetypes – common behaviour patterns that aid in diagnosing system structures underlying observable events – to analyse feedback loops and delays in European food environments. A complex review of 47 articles identified six archetypes: Fixes that fail, Shifting the burden, Escalation, Success to the successful, Tragedy of the commons, and Supply and demand. Expert panel discussions revealed the socio-political context sustaining these archetypes. The findings identify both systemic barriers and solution pathways to accelerate the protein transition.

The shift towards less meat and more plant-based consumption is vital for environmental quality, public health, animal welfare, and food security. So far, no studies have examined both the two-way interaction between supermarket supply and household demand, and the role of decision-making about meals within households. This study introduces the agent-based model MEET-eaters, a computational model representing supermarkets, households, and consumers, that was developed to explore these two-way interactions in the Dutch socio-cultural context. The model simulates the effect of supply that is unlimited, fixed, or responsive to the meal choices of households. The approaches to choosing meals are based on the Dutch context. Model development and assumptions were reviewed with experts to enhance model acceptance and understanding. Two interventions were tested, that aimed at either consumer meal preference or supermarket supply. Results show that supermarket supply and household demand both strongly influence the meal choice. Moreover, patterns in meal choices of households are similar under unlimited and responsive supply of supermarkets. The intervention aiming to change supply was most effective when animal-based options were restricted. Results from the intervention changing dietary preference shows that targeting either a large group at random or a smaller high-status group resulted in a similar reduction of animal-based and increase in plant-based meals. For shorter intervention durations, meal choice reverted to pre-intervention patterns once the interventions were discontinued. The results imply that the persistent high availability of animal-based (meat, fish, dairy) options under responsive supply weakens incentives for consumers to purchase plant-based options. In addition, targeting population groups based on status or size could result in more plant-based consumption. Overall, the findings suggest that long-term policies are required to achieve and sustain a shift towards more plant-based diets.