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Pesticides are ubiquitous environmental pollutants negatively affecting ecosystem and human health1,2. About 3 Tg of pesticides are used annually in agriculture to protect crops3. How much of these pesticides remain on land and reach the aquifer or the ocean is uncertain. Monitoring their environmental fate is challenging, and a detailed picture of their mobility in time and space is largely missing4. Here, we develop a process-based model accounting for the hydrology and biogeochemistry of the 92 most used agricultural pesticide active substances to assess their pathways through the principal catchments of the world and draw a near-present picture of the global land and river budgets, including discharge to oceans. Of the 0.94 Tg net annual pesticide input in 2015 used in this study, 82% is biologically degraded, 10% remains as residue in soil and 7.2% leaches below the root zone. Rivers receive 0.73 Gg of pesticides from their drainage at a rate of 10 to more than 100 kg yr−1km−1. By contrast to their fate in soil, only 1.1% of pesticides entering rivers are degraded along streams, exceeding safety levels (concentrations >1 μg l−1) in more than 13,000 km of river length, with 0.71 Gg of pesticide active ingredients released to oceans every year. Herbicides represent the prevalent pesticide residue on both land (72%) and river outlets (62%).

Mitigation pathways by Integrated Assessment Models (IAMs) describe future emissions that keep global warming below specific temperature limits and are compared with countries’ collective greenhouse gas (GHG) emission reduction pledges. This is needed to assess mitigation progress and inform emission targets under the Paris Agreement. Currently, however, a mismatch of ~5.5 GtCO2yr−1exists between the global land-use fluxes estimated with IAMs and from countries’ GHG inventories. Here we present a ‘Rosetta stone’ adjustment to translate IAMs’ land-use mitigation pathways to estimates more comparable with GHG inventories. This does not change the original decarbonization pathways, but reallocates part of the land sink to be consistent with GHG inventories. Adjusted cumulative emissions over the period until net zero for 1.5 or 2 °C limits are reduced by 120–192 GtCO2relative to the original IAM pathways. These differences should be taken into account to ensure an accurate assessment of progress towards the Paris Agreement.

Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum–maximum estimates: 12.2–23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9–17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2–11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies—particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O–climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.

Letter to the Editor

Dynamic crop‐growth models are used to project the effects of rising atmospheric CO2concentration and associated climate change on crop yields. Such model predictions are largely untested in the field, for lack of experimental data. We tested the CERES‐Wheat model, modified to include leaf‐level photosynthesis response to elevated CO2, using field data from 2 yr of Free‐Air Carbon Dioxide Enrichment (FACE) experiments with spring wheat (Triticum aestivumL. cv. Yecora Rojo) in Maricopa, AZ. Two irrigation treatments (well‐watered, WW; water‐deficit stressed, WS) and two atmospheric CO2concentrations (ambient, 350 (μmol mol−1; elevated, 550 (μmol mol−1) were simulated. The model was evaluated using measurements of crop phenology, aboveground dry matter (DM) production, grain yield, and evapotranspiration (ET). Model calculations of crop phenology were within 2 to 3 d of observed values under WW, ambient CO2conditions in both years. The model did not simulate the accelerated crop phenology (5–8 d at physiological maturity) observed in the WW and elevated CO2treatments, indicating the need to include effects of increased stomatal resistance on canopy temperature. Simulations of DM and grain yield were within 10% of measured values, except for a tendency to overcalculate DM response to CO2by 10 to 15% in Year 1 for WS treatments. The model undercalculated cumulative ET under WW conditions by 15%; model sensitivity analyses suggest that simulation of potential evapotranspiration (PET) was too low for this arid site. The model reproduced measured dynamics of CO2‐water interactions. Simulated reductions in water loss due to elevated CO2were about 4%, in agreement with measurements. The model simulated larger increases in DM production and yield due to elevated CO2under WS than under WW conditions. In Year 1, simulated crop response to CO2was 2% larger (measured: 3%) under WS than under WW conditions; in Year 2, it was 11% larger (measured: 9%). The ability to simulate CO2‐water interactions, though it needs to be further evaluated with additional experimental datasets, is an important attribute of models used to project crop yields under elevated CO2and climate change.