Nitrous oxide (N2O) is the most important stratospheric ozone-depleting agent based on current emissions and the third largest contributor to increased net radiative forcing. Increases in atmospheric N2O have been attributed primarily to enhanced soil N2O emissions. Critically, contributions from soils in the Northern High Latitudes (NHL, >50°N) remain poorly quantified despite their vulnerability to permafrost thawing induced by climate change. An ensemble of six terrestrial biosphere models suggests NHL soil N2O emissions doubled since the preindustrial 1860s, increasing on average by 2.0±1.0 Gg N yr-1 (p<0.01). This trend reversed after the 1980s because of reduced nitrogen fertilizer application in non-permafrost regions and increased plant growth due to CO2 fertilization suppressed emissions. However, permafrost soil N2O emissions continued increasing attributable to climate warming; the interaction of climate warming and increasing CO2 concentrations on nitrogen and carbon cycling will determine future trends in NHL soil N2O emissions.

We synthesized N2O emissions over North America using 17 bottom-up (BU) estimates from 1980-2016 and five top-down (TD) estimates from 1998-2016. The BU-based total emission shows a slight increase owing to U.S. agriculture, while no consistent trend is shown in TD estimates. During 2007-2016, North American N2O emissions are estimated at 1.7 (1.0-3.0) Tg N yr-1 (BU) and 1.3 (0.9-1.5) Tg N yr-1 (TD). Anthropogenic emissions were twice larger than natural fluxes from soil and water. Direct agricultural and industrial activities accounted for 68% of total anthropogenic emissions, 71% of which was contributed by the U.S. Our estimates of U.S. agricultural emissions are comparable to the EPA greenhouse gas (GHG) inventory, which includes estimates from IPCC tier 1 (emission factor) and tier 3 (process-based modeling) approaches. Conversely, our estimated agricultural emissions for Canada and Mexico are twice as large as the respective national GHG inventories based on tier 1 approaches.

Isoprene is the dominant non-methane organic compound emitted to the atmosphere, where it drives ozone and aerosol production, modulates atmospheric oxidation, and interacts with the global nitrogen cycle. Isoprene emissions are highly variable and uncertain, as is the non-linear chemistry coupling isoprene and its primary sink, the hydroxyl radical (OH). Space-based isoprene measurements can help close the gap on these uncertainties, and when combined with concurrent formaldehyde data provide a new constraint on atmospheric oxidation regimes. Here we present a next-generation machine-learning isoprene retrieval for the Cross-track Infrared Sounder (CrIS) that provides improved sensitivity, lower noise, and thus higher space-time resolution than earlier approaches. The Retrieval of Organics with CrIS Radiances (ROCR) isoprene measurements compare well with previous space-based retrievals as well as with the first-ever ground-based isoprene column measurements, with 20-50% discrepancies that reflect differing sources of systematic uncertainty. An ensemble of sensitivity tests points to the spectral background and isoprene profile specification as the most relevant uncertainty sources in the ROCR framework. We apply the ROCR isoprene algorithm to the full CrIS record from 2012-2020, showing that it can resolve fine-scale spatial gradients at daily resolution over the world’s isoprene hotspots. Results over North America and Amazonia highlight emergent connections between isoprene abundance and daily-to-interannual variations in temperature, nitrogen oxides, and drought stress.

Carbon monoxide (CO) is an ozone precursor, oxidant sink, and widely-used pollution tracer. The importance of anthropogenic versus other CO sources in the US is uncertain. Here we interpret extensive airborne measurements with an atmospheric model to constrain US fossil and non-fossil CO sources. Measurements reveal a low bias in the simulated CO background and a 30% overestimate of US fossil CO emissions in the 2016 National Emissions Inventory. After optimization we apply the model for source partitioning. During summer, regional fossil sources account for just 9-16% of the sampled boundary layer CO, and 32-38% of the North American enhancement-complicating use of CO as a fossil fuel tracer. The remainder predominantly reflects biogenic hydrocarbon oxidation plus fires. Fossil sources account for less domain-wide spatial variability at this time than non-fossil and background contributions. The regional fossil contribution rises in other seasons, and drives ambient variability downwind of urban areas.

The carbon cycle displays strong sensitivity to short term variations in environmental conditions, and it is key to understand how these variations are linked with variations in CO2 fluxes. Previously, atmospheric observations of CO2 have been sparse in many regions of the globe, making it challenging to evaluate these relationships. However, the OCO-2 satellite, launched in July 2014, provides new insight into global CO2 fluxes, particularly in regions that were previously difficult to monitor. In this study, we combine OCO-2 observations with a geostatistical inverse model to explore data-driven relationships between inferred CO2 flux patterns and environmental drivers. We further use year 2016 as an initial case study to explore the applicability of the geostatistical approach to large satellite-based inverse problems. We estimate daily, global CO2 fluxes at the model grid scale and find that a combination of air temperature, daily precipitation, and photosynthetically active radiation (PAR) best describe patterns in CO2 fluxes in most biomes across the globe. PAR is an adept predictor of fluxes across mid-to-high latitudes, whereas a combined set of daily air temperature and precipitation shows strong explanatory power across tropical biomes. However, we are unable to quantify a larger number of relationships between environmental drivers and CO2 fluxes using OCO-2 due to the limited sensitivity of total column satellite observations to detailed surface processes. Overall, we estimate a global net biospheric flux of -1.73 ± 0.53 GtC in year 2016, in close agreement with recent inverse modeling studies using OCO-2 retrievals as observational constraints.