Climate change and freshwater quality are well-linked. Changes in climate result in changes in streamflow and rising water temperatures, which impact biochemical reaction rates and increase stratification in lakes and reservoirs. Using two water quality modeling systems (the Hydrologic and Water Quality System; HAWQS and US Basins), five climate models, and two greenhouse gas (GHG) mitigation policies, we assess future water quality in the continental U.S. to 2100 considering four water quality parameters: water temperature, dissolved oxygen, total nitrogen, and total phosphorus. Once these parameters are aggregated into a water quality index, we find that, while the water quality models differ under the baseline, there is more agreement between future projections. In addition, we find that the difference in national-scale economic benefits across climate models is generally larger than the difference between the two water quality models. Both water quality models find that water quality will more likely worsen in the East than in the West. Under the business-as-usual emissions scenario, we find that climate change is likely to cause economic impacts ranging from 1.2 to 2.3 (2005 billion USD/year) in 2050 and 2.7 to 4.8 in 2090 across all climate and water quality models.

Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH₄) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH₄ emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches.

The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH₄ yr⁻¹ higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions.

The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained.

The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric ¹³CH₄. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH₄ growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH₄ emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric ¹³CH₄ observations.

In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

This article looks back at 25 years of achievements of the Global Trade Analysis Project (GTAP) from different angles. It covers the design features of the project and the collaboration in a global research network, the contributions GTAP has made to better informed trade policy making, its contributions in the area of environment and climate change and its capacity to absorb theoretical developments in applied modeling. The paper also makes some suggestions about future directions.