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The Community Earth System Model version 2 (CESM2) includes a detailed representation of chemistry throughout the atmosphere in the Community Atmosphere Model with chemistry and Whole Atmosphere Community Climate Model configurations. These model configurations use the Model for Ozone and Related chemical Tracers (MOZART) family of chemical mechanisms, covering the troposphere, stratosphere, mesosphere, and lower thermosphere. The new MOZART tropospheric chemistry scheme (T1) has a number of updates over the previous version (MOZART‐4) in CESM, including improvements to the oxidation of isoprene and terpenes, organic nitrate speciation, and aromatic speciation and oxidation and thus improved representation of ozone and secondary organic aerosol precursors. An evaluation of the present‐day simulations of CESM2 being provided for Climate Model Intercomparison Project round 6 (CMIP6) is presented. These simulations, using the anthropogenic and biomass burning emissions from the inventories specified for CMIP6, as well as online calculation of emissions of biogenic compounds, lightning NO, dust, and sea salt, indicate an underestimate of anthropogenic emissions of a variety of compounds, including carbon monoxide and hydrocarbons. The simulation of surface ozone in the southeast United States is improved over previous model versions, largely due to the improved representation of reactive nitrogen and organic nitrate compounds resulting in a lower ozone production rate than in CESM1 but still overestimates observations in summer. The simulation of tropospheric ozone agrees well with ozonesonde observations in many parts of the globe. The comparison of NOx and PAN to aircraft observations indicates the model simulates the nitrogen budget well. Plain Language Summary The set of chemical reactions for tropospheric chemistry used in the Community Earth System Model version 2 (CESM2) has been updated significantly over CESM1 in the Community Atmosphere Model with chemistry (CAM‐chem) and Whole Atmosphere Community Climate Model (WACCM) configurations. The emissions used for the CESM2 simulations are documented here, with anthropogenic and biomass burning emissions based on the specified inventories for Climate Model Intercomparison Project 6 (CMIP6), and emissions of biogenic compounds, lightning NO, dust, and sea salt are calculated online and dependent on the simulated meteorology. Evaluation of the CAM‐chem and WACCM configurations of CESM2 with observations indicate an underestimate of anthropogenic emissions of a variety of compounds, including carbon monoxide and hydrocarbons. The updated chemistry leads to an improvement in the simulation of tropospheric ozone. Key Points This paper fully documents the significant updates to the chemistry mechanisms in version 2 of the Community Earth System Model The new tropospheric chemistry scheme improves representation of isoprene oxidation as well as other ozone precursors over earlier versions The simulation of tropospheric ozone is improved in comparison to observations

Rising emissions from wildfires over recent decades in the Pacific Northwest are known to counteract the reductions in human-produced aerosol pollution over North America. Since amplified Pacific Northwest wildfires are predicted under accelerating climate change, it is essential to understand both local and transported contributions to air pollution in North America. Here, we find corresponding increases for carbon monoxide emitted from the Pacific Northwest wildfires and observe significant impacts on both local and down-wind air pollution. Between 2002 and 2018, the Pacific Northwest atmospheric carbon monoxide abundance increased in August, while other months showed decreasing carbon monoxide, so modifying the seasonal pattern. These seasonal pattern changes extend over large regions of North America, to the Central USA and Northeast North America regions, indicating that transported wildfire pollution could potentially impact the health of millions of people. Growing emissions from Pacific Northwest wildfires have increased atmospheric carbon monoxide in August, raising questions about potential health impacts as the seasonal pattern of air quality changes for large regions of North America.

This paper studies the seasonal variation of surface and column CO at three different sites (Paris, Jungfraujoch and Wollongong), with an emphasis on establishing a link between the CO vertical distribution and the nature of CO emission sources. We find the first evidence of a time lag between surface and free tropospheric CO seasonal variations in the Northern Hemisphere. The CO seasonal variability obtained from the total columns and free tropospheric partial columns shows a maximum around March–April and a minimum around September–October in the Northern Hemisphere (Paris and Jungfraujoch). In the Southern Hemisphere (Wollongong) this seasonal variability is shifted by about 6 months. Satellite observations by the IASI–MetOp (Infrared Atmospheric Sounding Interferometer) and MOPITT (Measurements Of Pollution In The Troposphere) instruments confirm this seasonality. Ground-based FTIR (Fourier transform infrared) measurements provide useful complementary information due to good sensitivity in the boundary layer. In situ surface measurements of CO volume mixing ratios at the Paris and Jungfraujoch sites reveal a time lag of the near-surface seasonal variability of about 2 months with respect to the total column variability at the same sites. The chemical transport model GEOS-Chem (Goddard Earth Observing System chemical transport model) is employed to interpret our observations. GEOS-Chem sensitivity runs identify the emission sources influencing the seasonal variation of CO. At both Paris and Jungfraujoch, the surface seasonality is mainly driven by anthropogenic emissions, while the total column seasonality is also controlled by air masses transported from distant sources. At Wollongong, where the CO seasonality is mainly affected by biomass burning, no time shift is observed between surface measurements and total column data.

Top-down observational constraints on emissions flux estimates from satellite observations of chemical composition are subject to biases and errors stemming from transport, chemistry and prior emissions estimates. In this context, we developed an ensemble data assimilation system to optimize the initial conditions for carbon monoxide (CO) and aerosols, while also quantifying the respective emission fluxes with a distinct attribution of anthropogenic and wildfire sources. We present the separate assimilation of CO profile v9 retrievals from the Measurements of Pollution in the Troposphere (MOPITT) instrument and Aerosol Optical Depth (AOD), collection 6.1, from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. This assimilation system is built on the Data Assimilation Research Testbed (DART) and includes a meteorological ensemble to assimilate weather observations within the online Community Atmosphere Model with Chemistry (CAM-chem). Inversions indicate an underestimation of CO emissions in CAMS-GLOB-ANT_v5.1 in China for 2015 and an overestimation of CO emissions in the Fire INventory from NCAR (FINN) version 2.2, especially in the tropics. These emissions increments are consistent between the MODIS AOD and the MOPITT CO-based inversions. Additional simulations and comparison with in situ observations from the NASA Atmospheric Tomography Mission (ATom) show that biases in hydroxyl radical (OH) chemistry dominate the CO errors.

Model intercomparison studies often report a large spread in simulation results, but quantifying the causes of these differences is hindered by the fact that several processes contribute to the model spread simultaneously. Here we use the Multi‐Scale Infrastructure for Chemistry and Aerosols (MUSICA) version 0 to investigate the model resolution dependencies of simulated chemical species, with a focus on the differences between global uniform grid and regional refinement grid simulations with the same modeling framework. We construct two global (ne30 [∼112 km] and ne60 [∼56 km]) and two regional refinement grids over Korea (ne30x8 [∼14 km] and ne30x16 [∼7 km]). The grid resolution can change chemical concentrations by an order of magnitude in the boundary layer, and the importance increases as the species' reactivity increases (e.g., up to 50% and 1,000% changes for ethane and xylenes, respectively). The diurnal cycle of oxidants (OH, O3, and NO3) also varies with the grid resolution, which leads to different oxidation pathways of volatile organic compounds (e.g., the fraction of monoterpenes reacting with NO3 in Seoul around midnight is 90% for ne30, but 65% for ne30x16). The models with high‐resolution grids usually do a better job at reproducing aircraft observations during the KORUS‐AQ campaign, but not always, implying compensating errors in the coarse grid simulations. For example, ozone is better reproduced by the coarse grid due to the artificial mixing of NOx. When developing new chemical mechanisms and evaluating models over urban areas, the uncertainties associated with model resolution should be considered. Plain Language Summary A new model framework, the Multi‐Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0), has been developed at NCAR to enable a computationally feasible global modeling framework while still resolving chemistry at urban scales. Using the MUSICAv0 framework with different horizontal grid resolutions (∼112, ∼56, ∼14, and ∼7 km), this work examines how much horizontal grid resolution can affect simulated chemical concentrations in 3D chemistry models. Model concentrations can vary up to 10 times between ∼112 and ∼7 km grids over urban areas at the surface. On the other hand, a region‐specific emission inventory with detailed local information is essential for some chemical species, although it is generally less important than the grid resolution for many chemical species. The model with a high‐resolution grid better reproduces observations in general, but in some cases compensating errors result in better comparisons for the coarse grid. This work suggests that the effects of grid resolution should not be ignored when evaluating new chemical mechanisms and chemistry models in future studies, and high grid resolution in 3D models is needed to simulate air pollutants over urban and downwind regions. Key Points The dependence of simulated chemical species on model resolution is quantified in a single modeling framework Model evaluations can be substantially affected by grid resolution, especially for urban surface and aircraft measurements at low altitudes Grid resolution strongly impacts the oxidation of volatile organic compounds through differences in diurnal variation of oxidants

Exposure to wildfire smoke is a well‐known concern for public health and is anticipated to worsen with an increase in wildfire activity related to climate change. This study uses satellite and ground‐based carbon monoxide (CO) measurements from 2004 to 2019 to evaluate a change in its seasonal cycle due to wildfire emissions. Monthly average CO total columns from the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument over Alberta and Ontario, and from a ground‐based Fourier transform infrared spectrometer in downtown Toronto are compared before and after 1 January 2012, following previous literature. Between the two time periods, a new peak emerges in the seasonal cycle of CO, centered around August. Monthly emergency room admissions from Alberta and Ontario for nine cardiovascular and respiratory diseases are assessed with a difference in difference analysis, using MOPITT CO as the exposure metric. This analysis was used to calculate the change in monthly hospital admissions per 100,000 people, given a 1 ppb increase in XCO post‐2012 compared to pre‐2012, along with the 95% confidence interval (CI). For Ontario, this term is positive and significant for hypertension (change = 1.88, CI = 1.18–2.57), ischemic heart disease (0.50, CI = 0.12–0.88), arrhythmia (0.12, CI = 0.03–0.22), and asthma (0.31, CI = 0.05–0.57). For Alberta, there is a significant and positive interaction for arrhythmia (0.48, CI = 0.12–0.85). These results indicate that there was a statistically significant increase in adverse health outcomes for five of the eighteen disease‐province pairings associated with the increase in atmospheric CO after 2011 coinciding with enhanced wildfire emissions. Plain Language Summary Previous literature has identified an increase of atmospheric carbon monoxide (CO) in the Pacific Northwest in August when considering the data before and after 2012, and linked this to forest fire activity in this region. In this study, a similar increase in CO was measured in the provinces of Alberta and Ontario, Canada using satellite data and in the city of Toronto using a ground‐based instrument. To determine whether the observed increase in CO has implications for public health, emergency room admissions for nine cardiovascular and respiratory diseases were examined over the same time period. The analysis used atmospheric CO as a measure of exposure and assessed differences between the pre‐2012 and post‐2012 periods. The findings are suggestive of a link between enhanced wildfire‐related CO concentrations after 2012 and worsening health outcomes, with statistically significant results for five of the eighteen disease‐province pairings. Key Points The mean total column CO for August in the provinces of Ontario and Alberta increased between 2004‐2011 and 2012–2019 due to forest fires Hospital admissions for cardiovascular and respiratory diseases show worsening health outcomes after 2012 for five disease‐province pairs CO is demonstrated to be a potential metric for smoke exposure in wildfire health studies

The increasing frequency and severity of wildfires due to climate change pose health risks to migrant farm workers laboring in wildfire‐prone regions. This study focuses on Sonoma County, California, investigating the effectiveness of air monitoring and safety protections for farmworkers. The analysis employs AirNow and PurpleAir PM2.5 data acquired during the 2020 wildfire season, comparing spatial variability in air pollution. Results show significant differences between the single Sonoma County AirNow station data and the PurpleAir data in the regions directly impacted by wildfire smoke. Three distinct wildfire pollution episodes with elevated PM2.5 levels are identified to examine the regional variations. This study also examines the system used to exempt farmworkers from wildfire mandatory evacuation orders, finding incomplete information, ad hoc decision‐making, and scant enforcement. In response, we make policy recommendations that include stricter requirements for employers, real‐time air quality monitoring, post‐exposure health screenings, and hazard pay. Our findings underscore the need for significant consideration of localized air quality readings and the importance of equitable disaster policies for protecting the health of farmworkers (particularly those who are undocumented migrants) in the face of escalating wildfire risks. Plain Language Summary In Sonoma County, California, wildfires and wildfire smoke are becoming more frequent and severe due to climate change. This study looks at how wildfire smoke could impact farmworkers, who often work outdoors. By comparing data from different air quality monitors during the 2020 Sonoma County wildfires, we found that farmworkers are exposed to high pollution levels, with some monitors showing more pollution than others. We also found that the system for deciding when farmworkers should labor during wildfires needs to be more consistent and adequately protect their health. Based on our findings, we recommend better air quality monitoring, improved policies to protect farmworkers during wildfires, and more support for those affected by the pollution. This research highlights the need to prioritize the health and safety of farmworkers, especially as wildfires become more common. Key Points The Agricultural Pass program challenges the safety of migrant farmworkers during extreme wildfires Regional variabilities in air quality emphasize the importance of localized measurements The use of local low‐cost sensor data with recommended filtering and smoke correction, enhances health and safety air quality monitoring

We present the Fire Inventory from National Center for Atmospheric Research (NCAR) version 2.5 (FINNv2.5), a fire emissions inventory that provides publicly available emissions of trace gases and aerosols for various applications, including use in global and regional atmospheric chemistry modeling. FINNv2.5 includes numerous updates to the FINN version 1 framework to better represent burned area, vegetation burned, and chemicals emitted. Major changes include the use of active fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375 m spatial resolution, which allows smaller fires to be included in the emissions processing. The calculation of burned area has been updated such that a more rigorous approach is used to aggregate fire detections, which better accounts for larger fires and enables using multiple satellite products simultaneously for emissions estimates. Fuel characterization and emissions factors have also been updated in FINNv2.5. Daily fire emissions for many trace gases and aerosols are determined for 2002–2019 (Moderate Resolution Imaging Spectroradiometer (MODIS)-only fire detections) and 2012–2019 (MODIS + VIIRS fire detections). The non-methane organic gas emissions are allocated to the species of several commonly used chemical mechanisms. We compare FINNv2.5 emissions against other widely used fire emissions inventories. The performance of FINNv2.5 emissions as inputs to a chemical transport model is assessed with satellite observations. Uncertainties in the emissions estimates remain, particularly in Africa and South America during August–October and in southeast and equatorial Asia in March and April. Recommendations for future evaluation and use are given.

Tropospheric ozone results from in situ chemical formation and stratosphere–troposphere exchange (STE), with the latter being more important in the middle and upper troposphere than in the lower troposphere. Ozone photochemical formation is nonlinear and results from the oxidation of methane and non-methane hydrocarbons (NMHCs) in the presence of nitrogen oxide (NOx=NO+NO2). Previous studies showed that O3 short- and long-term trends are nonlinearly controlled by near-surface anthropogenic emissions of carbon monoxide (CO), volatile organic compounds (VOCs), and nitrogen oxides, which may also be impacted by the long-range transport (LRT) of O3 and its precursors. In addition, several studies have demonstrated the important role of STE in enhancing ozone levels, especially in the midlatitudes. In this article, we investigate tropospheric ozone spatial variability and trends from 2005 to 2019 and relate those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the tropospheric column of ozone (TrC-O3) and its precursors, nitrogen dioxide (TrC-NO2), formaldehyde (TrC-HCHO), and total column CO (TC-CO), as well as ozonesonde data and model simulations. Our results indicate a complex relationship between tropospheric ozone column levels, surface ozone levels, and ozone precursors. While the increasing trends of near-surface ozone concentrations can largely be explained by variations in VOC and NOx concentration under different regimes, TrC-O3 may also be affected by other variables such as tropopause height and STE as well as LRT. Decreasing or increasing trends in TrC-NO2 have varying effects on TrC-O3, which is related to the different local chemistry in each region. We also shed light on the contribution of NOx lightning and soil NO and nitrous acid (HONO) emissions to trends of tropospheric ozone on regional and global scales.

We quantify future changes in wildfire burned area and carbon emissions in the 21st century under four Shared Socioeconomic Pathways (SSPs) scenarios and two SSP5-8.5-based solar geoengineering scenarios with a target surface temperature defined by SSP2-4.5 – solar irradiance reduction (G6solar) and stratospheric sulfate aerosol injections (G6sulfur) – and explore the mechanisms that drive solar geoengineering impacts on fires. This study is based on fully coupled climate–chemistry simulations with simulated occurrence of fires (burned area and carbon emissions) using the Whole Atmosphere Community Climate Model version 6 (WACCM6) as the atmospheric component of the Community Earth System Model version 2 (CESM2). Globally, total wildfire burned area is projected to increase over the 21st century under scenarios without geoengineering and decrease under the two geoengineering scenarios. By the end of the century, the two geoengineering scenarios have lower burned area and fire carbon emissions than not only their base-climate scenario SSP5-8.5 but also the targeted-climate scenario SSP2-4.5. Geoengineering reduces wildfire occurrence by decreasing surface temperature and wind speed and increasing relative humidity and soil water, with the exception of boreal regions where geoengineering increases the occurrence of wildfires due to a decrease in relative humidity and soil water compared with the present day. This leads to a global reduction in burned area and fire carbon emissions by the end of the century relative to their base-climate scenario SSP5-8.5. However, geoengineering also yields reductions in precipitation compared with a warming climate, which offsets some of the fire reduction. Overall, the impacts of the different driving factors are larger on burned area than fire carbon emissions. In general, the stratospheric sulfate aerosol approach has a stronger fire-reducing effect than the solar irradiance reduction approach.