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Besides the benefits of plant protection products (PPPs) for agricultural production, there is an increasing acknowledgement of the associated potential environmental risks. Here, we examine the feasibility of summarizing the extent of PPP usage at the country level, using Ireland as a case study, as well as at the European level. We used the area over which PPPs are applied (basic area) as an example variable that is relevant to initially assess the geographic extent of environmental risk. In Irish agricultural systems, which are primarily grass-based, herbicides fluroxypyr and glyphosate are the most widely applied active substances (ASs) in terms of basic area, followed by the fungicides chlorothalonil and prothioconazole that are closely associated with arable crops. Although all EU countries are subject to Regulation (EC) No 1185/2009, which sets the obligation of PPP usage data reporting at the national level, we only found usable data that met our criteria for Estonia, Germany, Finland, and Spain (4 of 30 countries reviewed). Overall, the most widely applied fungicide and herbicide in terms of basic area were prothioconazole (20%, 7% and 5% of national cultivated areas of Germany, Estonia and Ireland) and glyphosate (11%, 8% and 5% of national cultivated areas of Spain, Estonia and Ireland) respectively, although evaluations using application frequency may result in the observation of different trends. Several recommendations are proposed to tackle current data gaps and deficiencies in accessibility and usability of pesticide usage data across the EU in order to better inform environmental risk assessment and promote evidence-based policymaking.

An optimal network design was carried out to prioritise the installation or refurbishment of greenhouse gas (GHG) monitoring stations around Africa. The network was optimised to reduce the uncertainty in emissions across three of the most important GHGs: CO 2 , CH 4 , and N 2 O. Optimal networks were derived using incremental optimisation of the percentage uncertainty reduction achieved by a Gaussian Bayesian atmospheric inversion. The solution for CO 2 was driven by seasonality in net primary productivity. The solution for N 2 O was driven by activity in a small number of soil flux hotspots. The optimal solution for CH 4 was consistent over different seasons. All solutions for CO 2 and N 2 O placed sites in central Africa at places such as Kisangani, Kinshasa and Bunia (Democratic Republic of Congo), Dundo and Lubango (Angola), Zo et el e (Cameroon), Am Timan (Chad), and En Nahud (Sudan). Many of these sites appeared in the CH 4 solutions, but with a few sites in southern Africa as well, such as Amersfoort (South Africa). The multi-species optimal network design solutions tended to have sites more evenly spread-out, but concentrated the placement of new tall-tower stations in Africa between 10 N and 25 S. The uncertainty reduction achieved by the multi-species network of twelve stations reached 47.8% for CO 2 , 34.3% for CH 4 , and 32.5% for N 2 O. The gains in uncertainty reduction diminished as stations were added to the solution, with an expected maximum of less than 60%. A reduction in the absolute uncertainty in African GHG emissions requires these additional measurement stations, as well as additional constraint from an integrated GHG observatory and a reduction in uncertainty in the prior biogenic fluxes in tropical Africa.

Global population projections foresee the biggest increase to occur in Africa with most of the available uncultivated land to ensure food security remaining on the continent. Simultaneously, greenhouse gas emissions are expected to rise due to ongoing land use change, industrialisation, and transport amongst other reasons with Africa becoming a major emitter of greenhouse gases globally. However, distinct knowledge on greenhouse gas emissions sources and sinks as well as their variability remains largely unknown caused by its vast size and diversity and an according lack of observations across the continent. Thus, an environmental research infrastructure—as being setup in other regions—is more needed than ever. Here, we present the results of a design study that developed a blueprint for establishing such an environmental research infrastructure in Africa. The blueprint comprises an inventory of already existing observations, the spatial disaggregation of locations that will enable to reduce the uncertainty in climate forcing’s in Africa and globally as well as an overall estimated cost for such an endeavour of about 550 M€ over the next 30 years. We further highlight the importance of the development of an e-infrastructure, the necessity for capacity development and the inclusion of all stakeholders to ensure African ownership.