A multisectoral analysis that combines land use data with hydrological simulations reveals wide disparities in potential source water contamination.

Study reveals importance of accounting for micrometer scale distribution of substrates to predict carbon emissions from soil.

COVID-19 had multiple impacts on the electric sector and the nature of those impacts varied on the scale analyzed.

Improving predictability of water quality and nutrient cycling in large river systems.

Developing conceptual models for microbial-environmental–ecosystem interactions is key to enhancing the ability of models to predict future ecosystem function.

Researchers characterize protein signatures that indicate Acute Kidney Injury in COVID-19 patients.

Simulations reveal advantages of using new model vs. allometric scaling for risk assessment.

Research from the PNNL-led WHONDRS consortium reveals chemistry and spatial gradients of metabolomes from river water and sediments around the globe.

Using a novel settlement-related dataset produced more accurate population downscaling than using other, more traditional datasets.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Despite an increase in future electricity demands, virtual water trading in the U.S. electricity sector is expected to decline as renewable energy expands.

A multi-institutional team has obtained information about nanoscale interactions between the spike protein of the novel coronavirus SARS-CoV-2 and common household inorganic surfaces.

Exposure to polycyclic aromatic hydrocarbons found at Superfund Sites induces enzymes in dose- and time-dependent patterns in mice.

Soil moisture influences both the activity of soil DNA viruses, as well as the composition and abundance of RNA viruses.

A new microbial community model reveals previous exposure to hydrologic variation influences a species’ specialized biogeochemical functions.

Detailed characterization of molecules in, under, and along the Columbia River reveal potential mechanisms for biogeochemical cycling.

Integrating hydrogeology and biogeochemistry are required to model the dynamics of geochemical processes occurring in river corridor zones where groundwater and surface water mix.

Theoretical analysis reveals flow variations that happen over longer time periods affect a plume’s spread and center of mass.

Knowing which bacteria in a community are involved with carbon cycling could help scientists predict how microbial carbon storage and release could influence future climate dynamics.

Hypergraphs can more faithfully identify important genes in complex immune responses.