Strengthening our grip on food security by encoding physics into AI

Climate change will jeopardize food security. Food security involves the robustness of the global agri-food system. This agri-food system is intricately connected to systems centering around health, economy, social-cultural diversity, and global political stability. A systematic way to determine acceptable interventions in the global agri-food systems involves analyses at different spatial and temporal scales. Such multi-scale analyses are common within physics. Unfortunately, physics alone is not sufficient. Machine learning techniques may aid. We focus on neural networks (NN) into which physics-based information is encoded (PeNN) and apply it to a sub-problem within the agri-food system. We show that the mean squared error of the PeNN is always smaller than that of the NNs, in the order of a factor of thousand. Furthermore, the PeNNs capture extra and interpolation very well, contrary to the NNs. It is shown that PeNNs need a much smaller data set size than the NNs to achieve a similar mse. Our results suggest that the incorporation of physics into neural networks architectures yields promise for addressing food security

Sources, distribution, and acidity of sulfate-ammonium aerosol in the Arctic in winter-spring

We use GEOS-Chem chemical transport model simulations of sulfate-ammonium aerosol data from the NASA ARCTAS and NOAA ARCPAC aircraft campaigns in the North American Arctic in April 2008, together with longer-term data from surface sites, to better understand aerosol sources in the Arctic in winter-spring and the implications for aerosol acidity. Arctic pollution is dominated by transport from mid-latitudes, and we test the relevant ammonia and sulfur dioxide emission inventories in the model by comparison with wet deposition flux data over the source continents. We find that a complicated mix of natural and anthropogenic sources with different vertical signatures is responsible for sulfate concentrations in the Arctic. East Asian pollution influence is weak in winter but becomes important in spring through transport in the free troposphere. European influence is important at all altitudes but never dominant. West Asia (non-Arctic Russia and Kazakhstan) is the largest contributor to Arctic sulfate in surface air in winter, reflecting a southward extension of the Arctic front over that region. Ammonium in Arctic spring mostly originates from anthropogenic sources in East Asia and Europe, with added contribution from boreal fires, resulting in a more neutralized aerosol in the free troposphere than at the surface. The ARCTAS and ARCPAC data indicate a median aerosol neutralization fraction [NH^(+)_(4)]/(2[SO^(2-)_(4)] + [NO^(-)_(3)]) of 0.5 mol mol^(-1) below 2 km and 0.7 mol mol^(-1) above. We find that East Asian and European aerosol transported to the Arctic is mostly neutralized, whereas West Asian and North American aerosol is highly acidic. Growth of sulfur emissions in West Asia may be responsible for the observed increase in aerosol acidity at Barrow over the past decade. As global sulfur emissions decline over the next decades, increasing aerosol neutralization in the Arctic is expected, potentially accelerating Arctic warming through indirect radiative forcing and feedbacks