Climate change is the biggest global health threat of the 21st century. However, this challenge presents an opportunity to do things differently. This paper sets out how, using a design-led and collaborative approach, one can re-imagine the delivery of healthcare itself in a way that will deliver environmental sustainability. The paper presents a series of eight projects at the intersections of design, health and wellbeing, and complex net zero challenges, with an emphasis on inclusive, equitable, and sustainable design-led interventions. This encompasses diverse interventions across and beyond conventional design boundaries such as architecture, product design, and textile design providing insights that demonstrate the impact of design thinking, making, and acting on real-world net zero issues. Addressing such a broad and complex topic requires engagement across a wide range of stakeholders. The work undertaken has been conducted as part of a UK Government-funded Green Transition Ecosystem (GTE) Hub that has allowed multiple academic disciplines, research organisations, regional and local industry, and other public sector stakeholders, to connect with policy makers. Across seven themes, the paper describes how Design HOPES (Healthy Organisations in a Place-based Ecosystem, Scotland), as a design-led GTE Hub, brings in multiple and marginalised perspectives and how its design-led projects as one part of a wider movement for transformational change can re-use, nurture and develop these interventions sustainably. The overarching ambition being, through our collaborative design-led thinking, making, and acting, to build a more equitable and sustainable health and social care system across Scotland.

The agri-food sector is undergoing a comprehensive transformation as it transitions towards net zero. To achieve this, fundamental changes and innovations are required, including changes in how food is produced and delivered to customers, new technologies, data and physical infrastructures, and algorithmic advancements. In this paper, we explore the opportunities and challenges of deploying AI-based data infrastructures for sustainability in the agri-food sector by focusing on two case studies: soft-fruit production and brewery operations. We investigate the potential benefits of incorporating Internet of Things (IoT) sensors and AI technologies for improving the use of resources, reducing carbon footprints, and enhancing decision-making. We identify user engagement with new technologies as a key challenge, together with issues in data quality arising from environmental volatility, difficulties in generalising models, including those designed for carbon calculators, and socio-technical barriers to adoption. We highlight and advocate for user engagement, more granular availability of sensor, production, and emissions data, and more transparent carbon footprint calculations. Our proposed future directions include semantic data integration to enhance interoperability, the generation of synthetic data to overcome the lack of real-world farm data, and multi-objective optimisation systems to model the competing interests between yield and sustainability goals. In general, we argue that AI is not a silver bullet for net zero challenges in the agri-food industry, but at the same time, AI solutions, when appropriately designed and deployed, can be a useful tool when operating in synergy with other approaches.

Citizen Sensing, a correlative of Citizen Science, employs low-cost sensors to evidence local environmental issues and empowers citizens to use the data they collect. Whilst motivations for participation can vary, communities affected by pollution frequently have changemaking as their goal. Social innovation is closely aligned with citizen sensing, however the process of co-creating practices and solutions with citizens who wish to shape their world can be highly complex to design. Therefore, our research articulates an action-orientated framework which emerges from a 2-year pan European project by which follow-on communities may replicate sensing initiatives more easily. The authors examine five studies and explore the cross-cutting principles, phases, stakeholders, methods, and challenges which form this framework. The authors argue that whilst data collection and data awareness are crucial to the citizen sensing process, there are precursory and subsequent stages which are necessary to equip citizens to address complex environmental challenges and take action on them. Therefore, this paper focuses on the stages and methods which are distinctive to citizen sensing. It concludes with recommendations for future practice for citizen sensing and citizen science.

In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements (Dorigo et al., 2011b, a). The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonises them in terms of units and sampling rates, applies advanced quality control, and stores them in a database. Users can freely retrieve the data from this database through an online web portal (https://ismn.earth/en/, last access: 28 October 2021). Meanwhile, the ISMN has evolved into the primary in situ soil moisture reference database worldwide, as evidenced by more than 3000 active users and over 1000 scientific publications referencing the data sets provided by the network. As of July 2021, the ISMN now contains the data of 71 networks and 2842 stations located all over the globe, with a time period spanning from 1952 to the present. The number of networks and stations covered by the ISMN is still growing, and approximately 70 % of the data sets contained in the database continue to be updated on a regular or irregular basis. The main scope of this paper is to inform readers about the evolution of the ISMN over the past decade, including a description of network and data set updates and quality control procedures. A comprehensive review of the existing literature making use of ISMN data is also provided in order to identify current limitations in functionality and data usage and to shape priorities for the next decade of operations of this unique community-based data repository.

In different ways, Citizen Science and Remote Sensing (RS) have been recently developing as innovative and inclusive ways to improve data gathering and the comprehension of many environmental biophysical processes. In this framework, the GROW Observatory has been promoting the individual farmer awareness in agriculture as a counterpart to the ever-developing frequency and accuracy of RS products. In this analysis, 456 on-ground sensors from the GROW Observatory have been deployed in the Capitanata Irrigation Consortium (Apulia, Italy), with the aim of measuring the components of the water cycle with a dense, high-resolution pattern. The possibility of channelling these data into a high-resolution, plant-oriented Irrigation Water Need (IWN) parameter has been investigated, as a counterpart of coarser-resolution, spatially distributed monitoring powered by remote sensing and hydrological modelling. The instruments have the possibility of measuring three main variables: Surface Soil Moisture (at a maximum depth of 5 cm), Air temperature and Solar Illuminance (measured a few centimetres above ground). The monitoring period is July-October 2019, contemplating a wide range of different cultivation regimes. Irrigation water needs estimates has been obtained both in a point-wise (plant-oriented) and field-wise (spatial) format, in order to derive an irrigation water management tool. IWN and Surface Soil Moisture data are also employed in inferring back actual irrigation information from on-ground and RS data. These estimates have then be compared with observed data. Intermediate measure of Surface Soil Moisture, Air Temperature and radiation (by the Solar Illuminance proxy) have also been compared both with local measurements (those of and eddy-covariance station in place) and RS products from Sentinel and Landsat. Furthermore, Solar Illuminance data have been processed to extract a Leaf Area Index (LAI) product, also comparable with satellite estimates. These comparisons have been conducted through spatial and temporal correlations between the ground-gathered and remotely-sensed data. The potentiality and also the limitations of these low-cost instruments are presented and discussed.

This article reports on Citizen Observatories’ (COs) potential to contribute to the Sustainable Development Goals (SDGs), reflecting on the experience of the GROW Observatory (GROW). The research aims to take the first steps in closing the gap in the literature on COs’ potential contributions to the SDG framework, beyond quantitative data contributions for indicator monitoring. Following an analysis of project activities and outcomes mapped against the SDG framework, the findings reveal GROW’s potential contributions across two dimensions: (i) Actions to advance the implementation of goals and targets through awareness raising and training; participatory methods; multi-stakeholder connections; and supporting citizens to move from data to action and (ii) Data contributions to SDG indicator monitoring through citizen-generated datasets. While earlier research has focused mostly on the latter (dimension ii), CO activities can impact numerous goals and targets, highlighting their potential to relate global SDGs to local level action, and vice versa. These findings align with the growing literature on COs’ ability to bring together policy makers, scientists and citizens, and support changes to environmental policy and practice. Furthermore, this research suggests groundwork activities that address the goal and target level can also enhance sustained data collection to contribute to indicator level monitoring. We conclude with future trends and recommendations for COs wishing to contribute to the SDGs.

WeObserve delivered the first European-wide Citizen Observatory (CO) knowledge platform to share best practices, to address challenges and to inform practitioners, policy makers and funders of COs. We present key insights from WeObserve activities into leveraging challenges to create interlinked solutions, connecting with international frameworks and groups, advancing the field through communities of practice and practitioner networks, and fostering an enabling environment for COs. We also discuss how the new Horizon Europe funding programme can help to further advance the CO concept, and vice versa, how COs can provide a suitable mechanism to support the ambitions of Horizon Europe.

Citizen Science Projects: How to make a difference, is a massive open online course (MOOC). It was developed by the H2020 WeObserve project and ran on the FutureLearn platform from 2019. The course was designed to assist learners from all backgrounds and geographical locations to discover how to build their own citizen science project to address global challenges and create positive change. It also helped learners with interpreting the information they collected and using their findings to educate others about important local and global concerns. The main learning objectives for the course were: * Discover what citizen science and citizen observatories are * Engage with the general process of a citizen science project, the tools used and where they can be accessed * Collect and analyse data on relevant issues such as environmental challenges and disaster management, and discuss the results of their findings * Explore projects happening around the world, what the aims of these projects are and how learners could get involved * Model the steps to create their own citizen science project * Evaluate the potential of citizen science in bringing about change This course also provided five open-source, downloadable tools which have been tested in previous citizen science projects and created for the use of a wider range of projects. These tools are listed below and available in the research repository: * Empathy timeline tool * Community-level indicators tool * Data postcards tool * Future newspaper tool * Co-evaluation tool

This is an open-source downloadable tool that has been developed with community-led citizen science projects in mind. The Data Postcard tool is designed for community members and citizen science practitioners wanting to share the data they collect. It is a creative way to visualise and share data from a citizen science project. It can illustrate something simple, like the amount of times you walk through an area with high air pollution over the course of a week, or the kinds and amounts of animals you have observed in a prescribed area. This tool is designed for participants in a citizen science project once data have been collected; no previous experience of data visualisation is required.This page includes a Data Postcard guidance document which outlines the tool, the steps, resources needed and useful links that can explain the process of using the tool yourself. The page also includes a Data Postcard download, which can be used in conducting the activity.

Formalised knowledge systems, including universities and research institutes, are important for contemporary societies. They are, however, also arguably failing humanity when their impact is measured against the level of progress being made in stimulating the societal changes needed to address challenges like climate change. In this research we used a novel futures-oriented and participatory approach that asked what future envisioned knowledge systems might need to look like and how we might get there. Findings suggest that envisioned future systems will need to be much more collaborative, open, diverse, egalitarian, and able to work with values and systemic issues. They will also need to go beyond producing knowledge about our world to generating wisdom about how to act within it. To get to envisioned systems we will need to rapidly scale methodological innovations, connect innovators, and creatively accelerate learning about working with intractable challenges. We will also need to create new funding schemes, a global knowledge commons, and challenge deeply held assumptions. To genuinely be a creative force in supporting longevity of human and non-human life on our planet, the shift in knowledge systems will probably need to be at the scale of the enlightenment and speed of the scientific and technological revolution accompanying the second World War. This will require bold and strategic action from governments, scientists, civic society and sustained transformational intent.

This is an open-source downloadable tool that has been developed with community-led citizen science projects in mind. It is part of Citizen Sensing: A Toolkit, a collection of 25 methods and tools that can be used in citizen science projects.The Empathy Timeline tool is designed for community members and citizen science practitioners wanting to start a new project and is designed to be used at the beginning of a citizen science project. This Empathy Timeline method involves asking community members to think about the complexities of the shared issue they would like to monitor. The tool helps community members become aware of their own subjective viewpoints on environmental problems, as this approach allows participants to think about their own personal perceptions. This reflexivity can be achieved by having community members talk about the ways that they are affected by the issue, but also the ways that they contribute to it. An empathy timeline facilitates community building by bringing people together to discuss issues and consider them in a way that they perhaps have not often done before.This page includes an Empathy Timeline guidance document which outlines the tool, the steps, resources needed and useful links that can explain the process of using the tool yourself. The page also includes an Empathy Timeline canvas and a collection of sample shapes, both of which can be used in conducting the Empathy Timeline activity.

This is an open-source downloadable tool that has been developed with community-led citizen science projects in mind. It is part of Citizen Sensing: A Toolkit, a collection of 25 methods and tools that can be used in citizen science projects.The Future Newspaper tool is designed for community members and citizen science practitioners wanting to start their own project and is designed to be used at the end of a citizen science project. The Future Newspaper methods helps the creative reflection process by asking participants to imagine a variety of desirable futures. Then, by working backwards from those visions, participants can articulate the conditions, resources, stakeholders and events which might help lead to those outcomes. These can then become discussion points which the community can vote on to create actions and interventions. This page includes a Future Newspaper guidance document which outlines the tool, the steps, resources needed and useful links that can explain the process of using the toolkit yourself. The page also includes a Future Newspaper canvas to be used in conducting this activity.

Global soil moisture products retrieved from various sensors onboard satellites are becoming readily available. However, validation of such products is a crucial step to ensure their reliability. In-situ measurements, which provide the most accurate soil moisture estimates, are often used as reference dataset, but they are limited in number. The GROW Observatory (GROW) was initiated to demonstrate that a 'Citizens' Observatory' (CO) can provide and utilise unprecedented amounts of data. We present GROW as a case study and demonstrate, for the first time, the use of crowdsourced observations to assess the temporal and spatial consistency of various satellite-derived soil moisture products. In particular, we provide evidence of the added value to Earth Observation, thanks to (i) the high number of sensors deployed, covering a wide range of land use, environmental, and climatic conditions, and (ii) the unique spatial density in GROW. Our results confirmed that SMAP and ESA CCI SM can better capture the temporal dynamics compared to the other products investigated. We found high uncertainties due to the spatial mismatch between in-situ and satellite observations, not only for coarse scale but also for high-resolution soil moisture products. This finding highlights the importance of crowdsourced observations, which have the potential to reduce representativeness errors. Finally, a preliminary analysis of the spatial consistency of Sentinel-1 soil moisture showed a poor agreement against GROW data. We conclude presenting the challenges and the steps that will follow this preliminary analysis, as well as design guidelines for COs to meaningfully contribute to Earth Observation.