International audience | Arctic winter meteorology and orography in the Fairbanks North Star Borough (FNSB, interior Alaska) promote stably stratified boundary layers, often causing acute pollution episodes that exceed the US-EPA National Ambient Air Quality Standards. Power plant emission contributions to breathing level (0-10 m) pollution are estimated over the FNSB using highresolution Lagrangian tracer simulations run with temporally varying emissions and power plant plume rise accounting for atmospheric boundary layer stability and validated against comprehensive ALPACA-2022 observations. Average relative power plant contributions of 5-23% and 4-28% are diagnosed for SO 2 and NO x , respectively, with lower relative contributions in polluted conditions due to larger surface emissions. Highest population-weighted contributions are found in central and eastern (residential) areas of Fairbanks. Significant temporal variability in power plant contributions is revealed, depending on power plant operations and Arctic boundary layer stability. Vertical transport of power plant tracers to the surface depends on the interplay between the presence of temperature inversion layers and power plant stack heights as well as prevailing large-scale or local winds. Notably, power plant emissions can be transported to the surface even under strongly stable conditions, especially from shorter stacks, whereas down mixing from tall stacks mainly occurs under weakly stable conditions.

Ammonia volatilization from animal slurry applied to agricultural fields reduces nitrogen use efficiency in agriculture and pollutes the environment. This work presents new versions of a model and database focused on this route of N loss. The public ALFAM2 database (https://github.com/AU-BCE-EE/ALFAM2-data) was expanded with ammonia emission and ancillary measurements for >700 additional field plots. The ALFAM2 model (https://github.com/AU-BCE-EE/ALFAM2, https://zenodo.org/records/13312251) was extended with the addition of an ammonia sink for more plausible predictions over extended durations and to better reflect the expected reduction in emission rate several days after slurry application. A new parameter set was developed for the model taking into account the newly available measurement data. Model efficiency improved to 0.67 for the parameter estimation subset (0.52 for cross-validation) and mean absolute error was around 10% of applied total ammoniacal nitrogen. As in earlier versions, predicted emission is sensitive to application method, slurry dry matter and pH, air temperature, and wind speed. A collection of parameter sets for estimating uncertainty in average predictions was developed using a bootstrap approach. Predicted uncertainty is not trivial, and is high for some variable combinations, highlighting the challenge of making predictions based on available measurement data. Still, this work has resulted in more accurate, comprehensive, transparent, and flexible tools for emission inventory and related work on ammonia loss from field-applied slurry.

The System of Environmental-Economic Accounting (SEEA) remains neutral when it comes to the weak and strong sustainability worldviews. However, although its manuals do not contain any references to these concepts, it can support both through physical and monetary accounting. Given that strong sustainability is better suited to monitor environmental sustainability, we provide insights into how SEEA can contribute to promote the use of strong sustainability indicators.From a strong sustainability perspective, environmental sustainability requires identifying elements of natural capital to be preserved (critical natural capital) and at the level at which they should be preserved (reference values). SEEA and its manuals do not explicitly define the first element, but the concept of 'reference values' is implicitly embedded with the 'ecosystem condition accounts' introduced in the Ecosystem Accounting (EA) manual. As such, EA is the most relevant element of the SEEA in terms of advancing strong sustainability accounting. Given that ecosystem condition accounting is still in its early stages and that ecosystem condition is currently challenging to determine, three actions are proposed to better integrate strong sustainability in SEEA. First, the next revision of the SEEA Central Framework should be more explicit in how SEEA supports weak and strong sustainability. It should also consider how SEEA is linked to the wider indicator landscape (including the Sustainable Development Goals and the Global Biodiversity Framework). Second, ecosystem condition accounting needs to be further developed, as the more abundant extent accounts cannot capture the quality of ecosystems. Third, ecosystem condition accounting could build on other strong sustainability indicator initiatives such as Planetary Boundaries or the Environmental Sustainability Gap framework that have consistently integrated reference values in the accounting practices. These actions would provide additional means to interpret environmental sustainability beyond the direction of progress as is often the case.