Search

Large-scale reforestation, afforestation, and forest restoration schemes have gained global support as climate change mitigation strategies due to their significant carbon dioxide removal (CDR) potential. However, there has been limited research into the unintended consequences of forestation from a biophysical perspective. In the Community Earth System Model version 2 (CESM2), we apply a global forestation scenario, within a Paris Agreement-compatible warming scenario, to investigate the land surface and hydroclimate response. Compared to a control scenario where land use is fixed to present-day levels, the forestation scenario is up to 2 °C cooler at low latitudes by 2100, driven by a 10 % increase in evaporative cooling in forested areas. However, afforested areas where grassland or shrubland are replaced lead to a doubling of plant water demand in some tropical regions, causing significant decreases in soil moisture (∼ 5 % globally, 5 %–10 % regionally) and water availability (∼ 10 % globally, 10 %–15 % regionally) in regions with increased forest cover. While there are some increases in low cloud and seasonal precipitation over the expanded tropical forests, with enhanced negative cloud radiative forcing, the impacts on large-scale precipitation and atmospheric circulation are limited. This contrasts with the precipitation response to simulated large-scale deforestation found in previous studies. The forestation scenario demonstrates local cooling benefits without major disruption to global hydrodynamics beyond those already projected to result from climate change, in addition to the cooling associated with CDR. However, the water demands of extensive forestation, especially afforestation, have implications for its viability, given the uncertainty in future precipitation changes.

Wildfires can have a significant impact on air quality in Australia during severe burning seasons, but incomplete knowledge of the injection heights of smoke plumes poses a challenge for quantifying smoke exposure. In this study, we use two approaches to quantify the fractions of fire emissions injected above the planetary boundary layer (PBL), and we further investigate the impact of plume injection fractions on daily mean surface concentrations of fine particulate matter (PM2.5) from wildfire smoke in key cities over northern and southeastern Australia from 2009 to 2020. For the first method, we rely on climatological, monthly mean vertical profiles of smoke emissions from the Integrated Monitoring and Modelling System for wildland fires (IS4FIRES) together with assimilated PBL heights from NASA Modern-Era Retrospective Analysis for Research and Application (MERRA) version 2. For the second method, we develop a novel approach based on the Multi-angle Imaging SpectroRadiometer (MISR) observations and a random forest, machine learning model that allows us to directly predict the daily plume injection fractions above the PBL in each grid cell. We apply the resulting plume injection fractions quantified by the two methods to smoke PM2.5 concentrations simulated by the Stochastic Time-Inverted Lagrangian Transport (STILT) model in target cities. We find that characterization of the plume injection heights greatly affects estimates of surface daily smoke PM2.5, especially during severe wildfire seasons, when intense heat from fires can loft smoke high in the troposphere. However, using climatological injection profiles cannot capture well the spatiotemporal variability in plume injection fractions, resulting in a 63 % underestimation of daily fire emission fluxes injected above the PBL in comparison with those fluxes derived from MISR injection fractions. Our random forest model successfully reproduces the daily injected fire emission fluxes against MISR observations (R2=0.88, normalized mean bias = 10 %) and predicts that 27 % and 45 % of total fire emissions rise above the PBL in northern and southeastern Australia, respectively, from 2009 to 2020. Using the plume behavior predicted by the random forest method also leads to better model agreement with observed surface PM2.5 in several key cities near the wildfire source regions, with smoke PM2.5 accounting for 5 %–52 % of total PM2.5 during fire seasons from 2009 to 2020.

Surficial enhanced rock weathering (ERW) is a land-based carbon dioxide removal (CDR) strategy that involves applying crushed silicate rock (e.g., basalt) to agricultural soils. However, unintended biogeochemical interactions with the nitrogen cycle may arise through ERW increasing soil pH as basalt grains undergo dissolution that may reinforce, counteract, or even offset the climate benefits from carbon sequestration. Increases in soil pH could drive changes in the soil emissions of key non-CO2 greenhouse gases, e.g., nitrous oxide (N2O), and trace gases, e.g., nitric oxide (NO) and ammonia (NH3), that affect air quality and crop and human health. We present the development and implementation of a new improved nitrogen cycling scheme for the Community Land Model v5 (CLM5), the land component of the Community Earth System Model, allowing evaluation of ERW effects on soil gas emissions. We base the new parameterizations on datasets derived from soil pH responses of N2O, NO, and NH3 in ERW field trial and mesocosm experiments with crushed basalt. These new capabilities involve the direct implementation of routines within the CLM5 N cycle framework, along with asynchronous coupling of soil pH changes estimated through an ERW model. We successfully validated simulated “control” (i.e., no ERW) seasonal cycles of soil N2O, NO, and NH3 emissions against a wide range of global emission inventories. We benchmark simulated mitigation of soil N2O fluxes in response to ERW against a subset of data from ERW field trials in the US Corn Belt. Using the new scheme, we provide a specific example of the effect of large-scale ERW deployment with croplands on soil nitrogen fluxes across five key regions with high potential for CDR with ERW (North America, Brazil, Europe, India, and China). Across these regions, ERW implementation led to marked reductions in N2O and NO (both 18 %), with moderate increases in NH3 (2 %). While further developments are still required in our implementations when additional ERW data become available, our improved N cycle scheme within CLM5 has utility for investigating the potential of ERW point-source and regional effects of soil N2O, NO, and NH3 fluxes in response to current and future climates. This framework also provides the basis for assessing the implications of ERW for air quality given the role of NO in tropospheric ozone formation, as well as both NO and NH3 in inorganic aerosol formation.

Biogenic volatile organic compounds (BVOCs) influence atmospheric composition and climate, and their emissions are affected by changes in land use and land cover (LULC). Current Earth system models calculate BVOC emissions using parameterisations involving surface temperature, photosynthetic activity, CO2 and vegetation type and use emission factors (EFs) to represent the influence of vegetation on BVOC emissions. We present new EFs for the Interactive BVOC Emission Scheme (iBVOC) used in the United Kingdom Earth System Model (UKESM), based on those used by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 scheme. Our new EFs provide an alternative to the current EFs used in iBVOC, which are derived from older versions of MEGAN and the Organizing Carbon and Hydrology in Dynamic Ecosystem (ORCHIDEE) emission scheme. We show that current EFs used by iBVOC result in an overestimation of isoprene emissions from grasses, particularly C4 grasses, due to an oversimplification that incorporates the EF of shrubs (high isoprene emitters) into the EF for C3 and C4 grasses (low isoprene emitters). The current approach in iBVOCs assumes that C4 grasses are responsible for 40 % of total simulated isoprene emissions in the present day, which is much higher than other estimates of ∼ 0.3 %–10 %. Our new isoprene EFs substantially reduce the amount of isoprene emitted by C4 grasslands, in line with observational studies and other modelling approaches, while also improving the emissions from other known sources, such as tropical broadleaf trees. Similar results are found from the change to the terpene EF. With the new EFs, total global isoprene and terpene emissions are within the range suggested by the literature. While the existing model biases in the isoprene column are slightly exacerbated with the new EFs, other drivers of this bias are also noted. The disaggregation of shrub and grass EFs provides a more faithful description of the contribution of different vegetation types to BVOC emissions, which is critical for understanding BVOC emissions in the pre-industrial and under different future LULC scenarios, such as those involving wide-scale reforestation or deforestation. Our work highlights the importance of using updated and accurate EFs to improve the representation of BVOC emissions in Earth system models and provides a foundation for further improvements in this area.

Global ammonia (NH3) emission is expected to continue to rise due to intensified fertilization for growing food to satisfy the increasing demand worldwide. Previous studies have focused mainly on estimating the land-to-atmosphere NH3 injection but seldom addressed the other side of the bidirectional nitrogen exchange – deposition. Ignoring this significant input source of soil mineral nitrogen may lead to an underestimation of NH3 emissions from natural sources. Here, we used an Earth system model to quantify NH3-induced changes in atmospheric composition and the consequent impacts on the Earth's radiative budget and biosphere as well as the impacts of deposition on NH3 emissions from the land surface. We implemented a new scheme into the Community Land Model version 5 (CLM5) of the Community Earth System Model version 2 (CESM2) to estimate the volatilization of ammonium salt (NH4+) associated with synthetic and manure fertilizers into gaseous NH3. We further parameterized the amount of emitted NH3 captured in the plant canopy to derive a more accurate quantity of NH3 that escapes to the atmosphere. Our modified CLM5 estimated that 14 Tg N yr−1 of global NH3 emission is attributable to fertilizers. Interactively coupling terrestrial NH3 emissions to atmospheric chemistry simulations by the Community Atmospheric Model version 4 with chemistry (CAM4-chem), we found that such emissions favor the formation and deposition of NH4+ aerosol, which in turn influences the aerosol radiative effect and enhances soil NH3 volatilization in regions downwind of fertilized croplands. Our fully coupled simulations showed that global-total NH3 emission is enhanced by 3.3 Tg N yr−1 when 30 % more synthetic fertilizer is used compared to the 2000-level fertilization. In synergy with observations and emission inventories, our work provides a useful tool for stakeholders to evaluate the intertwined relations between agricultural trends, fertilizer use, NH3 emission, atmospheric aerosols, and climate so as to derive optimal strategies for securing both food production and environmental sustainability.

A range of applications analysing the impact of environmental changes due to climate change, e.g. geographical spread of climate-sensitive infections (CSIs) and agriculture crop modelling, make use of land surface modelling (LSM) to predict future land surface conditions. There are multiple LSMs to choose from that account for land processes in different ways and this may introduce predictive uncertainty when LSM outputs are used as inputs to inform a given application. For useful predictions for a specific application, one must therefore understand the inherent uncertainties in the LSMs and the variations between them, as well as uncertainties arising from variation in the climate data driving the LSMs. This requires methods to analyse multivariate spatio-temporal variations and differences. A methodology is proposed based on multiway data analysis, which extends singular value decomposition (SVD) to multidimensional tables and provides spatio-temporal descriptions of agreements and disagreements between LSMs for both historical simulations and future predictions. The application underlying this paper is prediction of how climate change will affect the spread of CSIs in the Fennoscandian and north-west Russian regions, and the approach is explored by comparing net primary production (NPP) estimates over the period 1998–2013 from versions of leading LSMs (JULES, CLM5 and two versions of ORCHIDEE) that are adapted to high-latitude processes, as well as variations in JULES up to 2100 when driven by 34 global circulation models (GCMs). A single optimal spatio-temporal pattern, with slightly different weights for the four LSMs (up to 14 % maximum difference), provides a good approximation to all their estimates of NPP, capturing between 87 % and 93 % of the variability in the individual models, as well as around 90 % of the variability in the combined LSM dataset. The next best adjustment to this pattern, capturing an extra 4 % of the overall variability, is essentially a spatial correction applied to ORCHIDEE-HLveg that significantly improves the fit to this LSM, with only small improvements for the other LSMs. Subsequent correction terms gradually improve the overall and individual LSM fits but capture at most 1.7 % of the overall variability. Analysis of differences between LSMs provides information on the times and places where the LSMs differ and by how much, but in this case no single spatio-temporal pattern strongly dominates the variability. Hence interpretation of the analysis requires the summation of several such patterns. Nonetheless, the three best principal tensors capture around 76 % of the variability in the LSM differences and to a first approximation successively indicate the times and places where ORCHIDEE-HLveg, CLM5 and ORCHIDEE-MICT differ from the other LSMs. Differences between the climate forcing GCMs had a marginal effect up to 6 % on NPP predictions out to 2100 without specific spatio-temporal GCM interaction.

Fire emissions are a critical component of carbon and nutrient cycles and strongly affect climate and air quality. Dynamic global vegetation models (DGVMs) with interactive fire modeling provide important estimates for long-term and large-scale changes in fire emissions. Here we present the first multi-model estimates of global gridded historical fire emissions for 1700–2012, including carbon and 33 species of trace gases and aerosols. The dataset is based on simulations of nine DGVMs with different state-of-the-art global fire models that participated in the Fire Modeling Intercomparison Project (FireMIP), using the same and standardized protocols and forcing data, and the most up-to-date fire emission factor table based on field and laboratory studies in various land cover types. We evaluate the simulations of present-day fire emissions by comparing them with satellite-based products. The evaluation results show that most DGVMs simulate present-day global fire emission totals within the range of satellite-based products. They can capture the high emissions over the tropical savannas and low emissions over the arid and sparsely vegetated regions, and the main features of seasonality. However, most models fail to simulate the interannual variability, partly due to a lack of modeling peat fires and tropical deforestation fires. Before the 1850s, all models show only a weak trend in global fire emissions, which is consistent with the multi-source merged historical reconstructions used as input data for CMIP6. On the other hand, the trends are quite different among DGVMs for the 20th century, with some models showing an increase and others a decrease in fire emissions, mainly as a result of the discrepancy in their simulated responses to human population density change and land use and land cover change (LULCC). Our study provides an important dataset for further development of regional and global multi-source merged historical reconstructions, analyses of the historical changes in fire emissions and their uncertainties, and quantification of the role of fire emissions in the Earth system. It also highlights the importance of accurately modeling the responses of fire emissions to LULCC and population density change in reducing uncertainties in historical reconstructions of fire emissions and providing more reliable future projections.

We characterise the vertical distribution of biomass-burning emissions across the Amazon during the biomass-burning season (July–November) with an extensive climatology of smoke plumes derived from MISR and MODIS (2005–2012) and CALIOP (2006–2012) observations. Smoke plume heights exhibit substantial variability, spanning a few hundred metres up to 6 km above the terrain. However, the majority of the smoke is located at altitudes below 2.5 km. About 60 % of smoke plumes are observed in drought years, 40 %–50 % at the peak month of the burning season (September) and 94 % over tropical forest and savanna regions, with respect to the total number of smoke plume observations. At the time of the MISR observations (10:00–11:00 LT), the highest plumes are detected over grassland fires (with an averaged maximum plume height of ∼1100 m) and the lowest plumes occur over tropical forest fires (∼800 m). A similar pattern is found later in the day (14:00–15:00 LT) with CALIOP, although at higher altitudes (2300 m grassland vs. 2000 m tropical forest), as CALIOP typically detects smoke at higher altitudes due to its later overpass time, associated with a deeper planetary boundary layer, possibly more energetic fires, and greater sensitivity to thin aerosol layers. On average, 3 %–20 % of the fires inject smoke into the free troposphere; this percentage tends to increase toward the end of the burning season (November: 15 %–40 %). We find a well-defined seasonal cycle between MISR plume heights, MODIS fire radiative power and atmospheric stability across the main biomes of the Amazon, with higher smoke plumes, more intense fires and reduced atmospheric stability conditions toward the end of the burning season. Lower smoke plume heights are detected during drought (800 m) compared to non-drought (1100 m) conditions, in particular over tropical forest and savanna fires. Drought conditions favour understory fires over tropical forest, which tend to produce smouldering combustion and low smoke injection heights. Droughts also seem to favour deeper boundary layers and the percentage of smoke plumes that reach the free troposphere is lower during these dry conditions. Consistent with previous studies, the MISR mid-visible aerosol optical depth demonstrates that smoke makes a significant contribution to the total aerosol loading over the Amazon, which in combination with lower injection heights in drought periods has important implications for air quality. This work highlights the importance of biome type, fire properties and atmospheric and drought conditions for plume dynamics and smoke loading. In addition, our study demonstrates the value of combining observations of MISR and CALIOP constraints on the vertical distribution of smoke from biomass burning over the Amazon.

Biomass burning is a significant source of trace gases and aerosols to the atmosphere, and the evolution of these species depends acutely on where they are injected into the atmosphere. GEOS-Chem is a chemical transport model driven by assimilated meteorological data that is used to probe a variety of scientific questions related to atmospheric composition, including the role of biomass burning. This paper presents the development and implementation of a new global biomass burning emissions injection scheme in the GEOS-Chem model. The new injection scheme is based on monthly gridded Multi-angle Imaging SpectroRadiometer (MISR) global plume-height stereoscopic observations in 2008. To provide specific examples of the impact of the model updates, we compare the output from simulations with and without the new MISR-based injection height scheme to several sets of observations from regions with active fires. Our comparisons with Arctic Research on the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) aircraft observations show that the updated injection height scheme can improve the ability of the model to simulate the vertical distribution of peroxyacetyl nitrate (PAN) and carbon monoxide (CO) over North American boreal regions in summer. We also compare a simulation for October 2010 and 2011 to vertical profiles of CO over the Amazon Basin. When coupled with larger emission factors for CO, a simulation that includes the new injection scheme also better matches selected observations in this region. Finally, the improved injection height improves the simulation of monthly mean surface CO over California during July 2008, a period with large fires.

Abstract Fine particulate matter (PM2.5) from U.S. anthropogenic sources is decreasing. However, previous studies have predicted that PM2.5 emissions from wildfires will increase in the midcentury to next century, potentially offsetting improvements gained by continued reductions in anthropogenic emissions. Therefore, some regions could experience worse air quality, degraded visibility, and increases in population‐level exposure. We use global climate model simulations to estimate the impacts of changing fire emissions on air quality, visibility, and premature deaths in the middle and late 21st century. We find that PM2.5 concentrations will decrease overall in the contiguous United States (CONUS) due to decreasing anthropogenic emissions (total PM2.5 decreases by 3% in Representative Concentration Pathway [RCP] 8.5 and 34% in RCP4.5 by 2100), but increasing fire‐related PM2.5 (fire‐related PM2.5 increases by 55% in RCP4.5 and 190% in RCP8.5 by 2100) offsets these benefits and causes increases in total PM2.5 in some regions. We predict that the average visibility will improve across the CONUS, but fire‐related PM2.5 will reduce visibility on the worst days in western and southeastern U.S. regions. We estimate that the number of deaths attributable to total PM2.5 will decrease in both the RCP4.5 and RCP8.5 scenarios (from 6% to 4–5%), but the absolute number of premature deaths attributable to fire‐related PM2.5 will double compared to early 21st century. We provide the first estimates of future smoke health and visibility impacts using a prognostic land‐fire model. Our results suggest the importance of using realistic fire emissions in future air quality projections.

Tropospheric ozone is one of the most hazardous air pollutants as it harms both human health and plant productivity. Foliage uptake of ozone via dry deposition damages photosynthesis and causes stomatal closure. These foliage changes could lead to a cascade of biogeochemical and biogeophysical effects that not only modulate the carbon cycle, regional hydrometeorology and climate, but also cause feedbacks onto surface ozone concentration itself. In this study, we implement a semi-empirical parameterization of ozone damage on vegetation in the Community Earth System Model to enable online ozone–vegetation coupling, so that for the first time ecosystem structure and ozone concentration can coevolve in fully coupled land–atmosphere simulations. With ozone–vegetation coupling, present-day surface ozone is simulated to be higher by up to 4–6 ppbv over Europe, North America and China. Reduced dry deposition velocity following ozone damage contributes to ∼ 40–100 % of those increases, constituting a significant positive biogeochemical feedback on ozone air quality. Enhanced biogenic isoprene emission is found to contribute to most of the remaining increases, and is driven mainly by higher vegetation temperature that results from lower transpiration rate. This isoprene-driven pathway represents an indirect, positive meteorological feedback. The reduction in both dry deposition and transpiration is mostly associated with reduced stomatal conductance following ozone damage, whereas the modification of photosynthesis and further changes in ecosystem productivity are found to play a smaller role in contributing to the ozone–vegetation feedbacks. Our results highlight the need to consider two-way ozone–vegetation coupling in Earth system models to derive a more complete understanding and yield more reliable future predictions of ozone air quality.

The Community Earth System Model (CESM1) CAM4-chem has been used to perform the Chemistry Climate Model Initiative (CCMI) reference and sensitivity simulations. In this model, the Community Atmospheric Model version 4 (CAM4) is fully coupled to tropospheric and stratospheric chemistry. Details and specifics of each configuration, including new developments and improvements are described. CESM1 CAM4-chem is a low-top model that reaches up to approximately 40 km and uses a horizontal resolution of 1.9° latitude and 2.5° longitude. For the specified dynamics experiments, the model is nudged to Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. We summarize the performance of the three reference simulations suggested by CCMI, with a focus on the last 15 years of the simulation when most observations are available. Comparisons with selected data sets are employed to demonstrate the general performance of the model. We highlight new data sets that are suited for multi-model evaluation studies. Most important improvements of the model are the treatment of stratospheric aerosols and the corresponding adjustments for radiation and optics, the updated chemistry scheme including improved polar chemistry and stratospheric dynamics and improved dry deposition rates. These updates lead to a very good representation of tropospheric ozone within 20 % of values from available observations for most regions. In particular, the trend and magnitude of surface ozone is much improved compared to earlier versions of the model. Furthermore, stratospheric column ozone of the Southern Hemisphere in winter and spring is reasonably well represented. All experiments still underestimate CO most significantly in Northern Hemisphere spring and show a significant underestimation of hydrocarbons based on surface observations.

Landscape fires produce smoke containing a very wide variety of chemical species, both gases and aerosols. For larger, more intense fires that produce the greatest amounts of emissions per unit time, the smoke tends initially to be transported vertically or semi-vertically close by the source region, driven by the intense heat and convective energy released by the burning vegetation. The column of hot smoke rapidly entrains cooler ambient air, forming a rising plume within which the fire emissions are transported. The characteristics of this plume, and in particular the height to which it rises before releasing the majority of the smoke burden into the wider atmosphere, are important in terms of how the fire emissions are ultimately transported, since for example winds at different altitudes may be quite different. This difference in atmospheric transport then may also affect the longevity, chemical conversion, and fate of the plumes chemical constituents, with for example very high plume injection heights being associated with extreme long-range atmospheric transport. Here we review how such landscape-scale fire smoke plume injection heights are represented in larger-scale atmospheric transport models aiming to represent the impacts of wildfire emissions on component of the Earth system. In particular we detail (i) satellite Earth observation data sets capable of being used to remotely assess wildfire plume height distributions and (ii) the driving characteristics of the causal fires. We also discuss both the physical mechanisms and dynamics taking place in fire plumes and investigate the efficiency and limitations of currently available injection height parameterizations. Finally, we conclude by suggesting some future parameterization developments and ideas on Earth observation data selection that may be relevant to the instigation of enhanced methodologies aimed at injection height representation.

The Community Atmosphere Model (CAM), version 5, is now coupled to extensive tropospheric and stratospheric chemistry, called CAM5-chem, and is available in addition to CAM4-chem in the Community Earth System Model (CESM) version 1.2. The main focus of this paper is to compare the performance of configurations with internally derived "free running" (FR) meteorology and "specified dynamics" (SD) against observations from surface, aircraft, and satellite, as well as understand the origin of the identified differences. We focus on the representation of aerosols and chemistry. All model configurations reproduce tropospheric ozone for most regions based on in situ and satellite observations. However, shortcomings exist in the representation of ozone precursors and aerosols. Tropospheric ozone in all model configurations agrees for the most part with ozonesondes and satellite observations in the tropics and the Northern Hemisphere within the variability of the observations. Southern hemispheric tropospheric ozone is consistently underestimated by up to 25%. Differences in convection and stratosphere to troposphere exchange processes are mostly responsible for differences in ozone in the different model configurations. Carbon monoxide (CO) and other volatile organic compounds are largely underestimated in Northern Hemisphere mid-latitudes based on satellite and aircraft observations. Nitrogen oxides (NOx) are biased low in the free tropical troposphere, whereas peroxyacetyl nitrate (PAN) is overestimated in particular in high northern latitudes. The present-day methane lifetime estimates are compared among the different model configurations. These range between 7.8 years in the SD configuration of CAM5-chem and 8.8 years in the FR configuration of CAM4-chem and are therefore underestimated compared to observational estimations. We find that differences in tropospheric aerosol surface area between CAM4 and CAM5 play an important role in controlling the burden of the tropical tropospheric hydroxyl radical (OH), which causes differences in tropical methane lifetime of about half a year between CAM4-chem and CAM5-chem. In addition, different distributions of NOx from lightning explain about half of the difference between SD and FR model versions in both CAM4-chem and CAM5-chem. Remaining differences in the tropical OH burden are due to enhanced tropical ozone burden in SD configurations compared to the FR versions, which are not only caused by differences in chemical production or loss but also by transport and mixing. For future studies, we recommend the use of CAM5-chem configurations, due to improved aerosol description and inclusion of aerosol–cloud interactions. However, smaller tropospheric surface area density in the current version of CAM5-chem compared to CAM4-chem results in larger oxidizing capacity in the troposphere and therefore a shorter methane lifetime.

We use a global coupled chemistry–climate–land model (CESM) to assess the integrated effect of climate, emissions and land use changes on annual surface O3 and PM2.5 in the United States with a focus on national parks (NPs) and wilderness areas, using the RCP4.5 and RCP8.5 projections. We show that, when stringent domestic emission controls are applied, air quality is predicted to improve across the US, except surface O3 over the western and central US under RCP8.5 conditions, where rising background ozone counteracts domestic emission reductions. Under the RCP4.5 scenario, surface O3 is substantially reduced (about 5 ppb), with daily maximum 8 h averages below the primary US Environmental Protection Agency (EPA) National Ambient Air Quality Standards (NAAQS) of 75 ppb (and even 65 ppb) in all the NPs. PM2.5 is significantly reduced in both scenarios (4 μg m−3; ~50%), with levels below the annual US EPA NAAQS of 12 μg m−3 across all the NPs; visibility is also improved (10–15 dv; >75 km in visibility range), although some western US parks with Class I status (40–74 % of total sites in the US) are still above the 2050 planned target level to reach the goal of natural visibility conditions by 2064. We estimate that climate-driven increases in fire activity may dominate summertime PM2.5 over the western US, potentially offsetting the large PM2.5 reductions from domestic emission controls, and keeping visibility at present-day levels in many parks. Our study indicates that anthropogenic emission patterns will be important for air quality in 2050. However, climate and land use changes alone may lead to a substantial increase in surface O3 (2–3 ppb) with important consequences for O3 air quality and ecosystem degradation at the US NPs. Our study illustrates the need to consider the effects of changes in climate, vegetation, and fires in future air quality management and planning and emission policy making.

The Pico Mountain Observatory, located at 2225 m a.s.l. in the Azores Islands, was established in 2001 to observe long-range transport from North America to the central North Atlantic. In previous research conducted at the observatory, ozone enhancement (> 55 ppbv) in North American outflows was observed, and efficient ozone production in these outflows was postulated. This study is focused on determining the causes for high d[O3] / d[CO] values (~1 ppbv ppbv−1) observed in the summers of 2009 and 2010. The folded retroplume technique, developed by Owen and Honrath (2009), was applied to combine upwind FLEXPART transport pathways with GEOS-Chem chemical fields. The folded result provides a semi-Lagrangian view of polluted North American outflow in terms of physical properties and chemical processes, including production/loss rate of ozone and NOx produced by lightning and thermal decomposition of peroxy acetyl nitrate (PAN). Two transport events from North America were identified for detailed analysis. High d[O3] / d[CO] was observed in both events, but due to differing transport mechanisms, ozone production tendency differed between the two. A layer of net ozone production was found at 2 km a.s.l. over the Azores in the first event plume, apparently driven by PAN decomposition during subsidence of air mass in the Azores–Bermuda High. In the second event, net ozone loss occurred during transport in the lower free troposphere, yet observed d[O3] / d[CO] was high. We estimate that in both events, CO loss through oxidation contributed significantly to d[O3] / d[CO] enhancement. Thus, it is not appropriate to use CO as a passive tracer of pollution in these events. In general, use of d[O3] / d[CO] as an indicator of net ozone production/loss may be invalid for any situation in which oxidants are elevated. Based on our analysis, use of d[O3] / d[CO] to diagnose ozone enhancement without verifying the assumption of negligible CO loss is not advisable.

In situ measurements of carbon monoxide (CO) and ozone (O3) at the Pico Mountain Observatory (PMO) located in the Azores, Portugal, are analyzed together with results from an atmospheric chemical transport model (GEOS-Chem) and satellite remote sensing data (AIRS (Atmospheric Infrared Sounder) for CO, and TES (Tropospheric Emission Spectrometer) for O3) to examine the evolution of free-troposphere CO and O3 over the North Atlantic for 2001–2011. GEOS-Chem captured the seasonal cycles for CO and O3 well but significantly underestimated the mixing ratios of CO, particularly in spring. Statistically significant (using a significance level of 0.05) decreasing trends were found for both CO and O3 based on harmonic regression analysis of the measurement data. The best estimates of the possible trends for CO and O3 measurements are −0.31 ± 0.30 (2-σ) ppbv yr−1 and −0.21 ± 0.11 (2-σ) ppbv yr−1, respectively. Similar decreasing trends for both species were obtained with GEOS-Chem simulation results. The most important factor contributing to the decreases in CO and O3 at PMO over the past decade is the decline in anthropogenic emissions from North America, which more than compensate for the impacts from increasing Asian emissions. It is likely that climate change in the past decade has also affected the intercontinental transport of O3.

We analyze the record of aerosol optical depth (AOD) measured by the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite in combination with surface PM2.5 to investigate the impact of fires on aerosol loading and air quality over Colorado from 2000 to 2012, and to evaluate the contribution of local versus transported smoke. Fire smoke contributed significantly to the AOD levels observed over Colorado. During the worst fire seasons of 2002 and 2012, average MODIS AOD over the Colorado Front Range corridor were 20–50% larger than the other 11 yr studied. Surface PM2.5 was also unusually elevated during fire events and concentrations were in many occasions above the daily National Ambient Air Quality Standard (35 μg m−3) and even reached locally unhealthy levels (> 100 μg m−3) over populated areas during the 2012 High Park fire and the 2002 Hayman fire. Over the 13 yr examined, long-range transport of smoke from northwestern US and even California (> 1500 km distance) occurred often and affected AOD and surface PM2.5. During most of the transport events, MODIS AOD and surface PM2.5 were reasonable correlated (r2 = 0.2–0.9), indicating that smoke subsided into the Colorado boundary layer and reached surface levels. However, that is not always the case since at least one event of AOD enhancement was disconnected from the surface (r22.5 levels). Observed plume heights from the Multi-angle Imaging SpectroRadiometer (MISR) satellite instrument and vertical aerosol profiles measured by the space-based Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) showed a complex vertical distribution of smoke emitted by the High Park fire in 2012. Smoke was detected from a range of 1.5 to 7.5 km altitude at the fire origin and from ground levels to 12.3 km altitude far away from the source. The variability of smoke altitude as well as the local meteorology were key in determining the aerosol loading and air quality over the Colorado Front Range region. Our results underline the importance of accurate characterization of the vertical distribution of smoke for estimating the air quality degradation associated with fire activity and its link to human health.

We analyze an extensive record of aerosol smoke plume heights derived from observations over North America for the fire seasons of 2002 and 2004–2007 made by the Multi-angle Imaging SpectroRadiometer (MISR) instrument on board the NASA Earth Observing System Terra satellite. We characterize the magnitude and variability of smoke plume heights for various biomes, and assess the contribution of local atmospheric and fire conditions to this variability. Plume heights are highly variable, ranging from a few hundred meters up to 5000 m above the terrain at the Terra overpass time (11:00–14:00 local time). The largest plumes are found over the boreal region (median values of ~850 m height, 24 km length and 940 m thickness), whereas the smallest plumes are found over cropland and grassland fires in the contiguous US (median values of ~530 m height, 12 km length and 550–640 m thickness). The analysis of plume heights in combination with assimilated meteorological observations from the NASA Goddard Earth Observing System indicates that a significant fraction (4–12%) of plumes from fires are injected above the boundary layer (BL), consistent with earlier results for Alaska and the Yukon Territories during summer 2004. Most of the plumes located above the BL (>83%) are trapped within stable atmospheric layers. We find a correlation between plume height and the MODerate resolution Imaging Spectroradiometer (MODIS) fire radiative power (FRP) thermal anomalies associated with each plume. Smoke plumes located in the free troposphere (FT) exhibit larger FRP values (1620–1640 MW) than those remaining within the BL (174–465 MW). Plumes located in the FT without a stable layer reach higher altitudes and are more spread-out vertically than those associated with distinct stable layers (2490 m height and 2790 m thickness versus 1880 m height and 1800 m thickness). The MISR plume climatology exhibits a well-defined seasonal cycle of plume heights in boreal and temperate biomes, with greater heights during June–July. MODIS FRP measurements indicate that larger summertime heights are the result of higher fire intensity, likely due to more severe fire weather during these months. This work demonstrates the significant effect of fire intensity and atmospheric structure on the ultimate rise of fire emissions, and underlines the importance of considering such physical processes in modeling smoke dispersion.

Ten-year observations of trace gases at Pico Mountain Observatory (PMO), a free troposphere site in the central North Atlantic, were classified by transport patterns using the Lagrangian particle dispersion model, FLEXPART. The classification enabled identifying trace gas mixing ratios associated with background air and long- range transport of continental emissions, which were defined as chemical signatures. Comparison between the chemical signatures revealed the impacts of natural and anthropogenic sources, as well as chemical and physical processes during long transport, on air composition in the remote North Atlantic. Transport of North American anthropogenic emissions (NA-Anthro) and summertime wildfire plumes (Fire) significantly enhanced CO and O3 at PMO. Summertime CO enhancements caused by NA-Anthro were found to have been decreasing by a rate of 0.67 ± 0.60 ppbv/year in the ten-year period, due possibly to reduction of emissions in North America. Downward mixing from the upper troposphere and stratosphere due to the persistent Azores-Bermuda anticyclone causes enhanced O3 and nitrogen oxides. The 'd' [O3]/'d' [CO] value was used to investigate O3 sources and chemistry in different transport patterns. The transport pattern affected by Fire had the lowest 'd' [O3]/'d' [CO], which was likely due to intense CO production and depressed O3 production in wildfire plumes. Slightly enhanced O3 and 'd' [O3]/'d' [CO] were found in the background air, suggesting that weak downward mixing from the upper troposphere is common at PMO. Enhancements of both butane isomers were found during upslope flow periods, indicating contributions from local sources. The consistent ratio of butane isomers associated with the background air and NA-anthro implies no clear difference in the oxidation rates of the butane isomers during long transport. Based on observed relationships between non-methane hydrocarbons, the averaged photochemical age of the air masses at PMO was estimated to be 11 ± 4 days.

Air pollution induced by fine particulate matter with diameter ≤ 2.5 μm (PM 2.5 ) poses a significant challenge for global air quality management. Understanding how factors such as climate change, land use and land cover change (LULCC), and changing emissions interact to impact PM 2.5 remains limited. To address this gap, we employed the Community Earth System Model and examined both the individual and combined effects of these factors on global surface PM 2.5 in 2010 and projected scenarios for 2050 under different Shared Socioeconomic Pathways (SSPs). Our results reveal biomass-burning and anthropogenic emissions as the primary drivers of surface PM 2.5 across all SSPs. Less polluted regions like the US and Europe are expected to experience substantial PM 2.5 reduction in all future scenarios, reaching up to ~5 μg m -3 (70 %) in SSP1. However, heavily polluted regions like India and China may experience varied outcomes, with a potential decrease in SSP1 and increase under SSP3. Eastern China witness ~20 % rise in PM 2.5 under SSP3, while northern India may experience ~70 % increase under same scenario. Depending on the region, climate change alone is expected to change PM 2.5 up to ±5 μg m -3 , while the influence of LULCC appears even weaker. The modest changes in PM 2.5 attributable to LULCC and climate change are associated with aerosol chemistry and meteorological effects, including biogenic volatile organic compound emissions, SO 2 oxidation, and NH 4 NO 3 formation. Despite their comparatively minor role, LULCC and climate change can still significantly shape future air quality in specific regions, potentially counteracting the benefits of emission control initiatives. This study underscores the pivotal role of changes in anthropogenic emissions in shaping future PM 2.5 across all SSP scenarios. Thus, addressing all contributing factors, with a primary focus on reducing anthropogenic emissions, is crucial for achieving sustainable reduction in surface PM 2.5 levels and meeting sustainable pollution mitigation goals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Terrestrial enhanced weathering (EW) of silicate rocks, such as crushed basalt, on farmlands is a promising scalable atmospheric carbon dioxide removal (CDR) strategy that urgently requires performance assessment with commercial farming practices. We report findings from a large-scale replicated EW field trial across a typical maize-soybean rotation on an experimental farm in the heart of the United Sates Corn Belt over 4 y (2016 to 2020). We show an average combined loss of major cations (Ca 2+ and Mg 2+ ) from crushed basalt applied each fall over 4 y (50 t ha -1 y -1 ) gave a conservative time-integrated cumulative CDR potential of 10.5 ± 3.8 t CO 2 ha -1 . Maize and soybean yields increased significantly ( P < 0.05) by 12 to 16% with EW following improved soil fertility, decreased soil acidification, and upregulation of root nutrient transport genes. Yield enhancements with EW were achieved with significantly ( P < 0.05) increased key micro- and macronutrient concentrations (including potassium, magnesium, manganese, phosphorus, and zinc), thus improving or maintaining crop nutritional status. We observed no significant increase in the content of trace metals in grains of maize or soybean or soil exchangeable pools relative to controls. Our findings suggest that widespread adoption of EW across farming sectors has the potential to contribute significantly to net-zero greenhouse gas emissions goals while simultaneously improving food and soil security., Competing Interests: Competing interests statement:D.J.B. has a minority equity stake in Future Forest/Undo, and is a member of the Advisory Board of The Carbon Community, a UK carbon removal charity, and the Scientific Advisory Council of the non-profit Carbon Technology Research Foundation. J.S.J. is funded through the public benefit corporation, Mati Carbon, a subsidiary of the not for profit Swaniti Initiative. N.J.P and C.T.R were co-founders of the CDR company Lithos Carbon, but have no remaining financial ties to the company. The remaining authors declare that they have no competing interests.

Surface ozone (O 3 ) is a major air pollutant and greenhouse gas with significant risks to human health, vegetation, and climate. Uncertainties around the impacts of various critical factors on O 3 is crucial to understand. We used the Community Earth System Model to investigate the impacts of land use and land cover change (LULCC), climate, and emissions on global O 3 air quality under selected Shared Socioeconomic Pathways (SSPs). Our findings show that increasing forest cover by 20 % under SSP1 in East China, Europe, and the eastern US leads to higher isoprene emissions leading 2-5 ppb increase in summer O 3 levels. Climate-induced meteorological changes, like rising temperatures, further enhance BVOC emissions and increase O 3 levels by 10-20 ppb in urban areas with high NO x levels. However, higher BVOC emissions can reduce O 3 levels by 5-10 ppb in remote environments. Future NO x emissions control reduces O 3 levels by 5-20 ppb in the US and Europe in all SSPs, but reductions in NO x and changes in oxidant titration increase O 3 in southeast China in SSP5. Increased NO x emissions in southern Africa and India significantly elevate O 3 levels up to 15 ppb under different SSPs. Climate change is equally important as emissions changes, sometimes countering the benefits of emissions control. The combined effects of emissions, climate, and land cover result in worse O 3 air quality in northern India (+40 %) and East China (+20 %) under SSP3 due to anthropogenic NO x and climate-induced BVOC emissions. Over the northern hemisphere, surface O 3 decreases due to reduced NO x emissions, although climate and land use changes can increase O 3 levels regionally. By 2050, O 3 levels in most Asian regions exceed the World Health Organization safety limit for over 150 days per year. Our study emphasizes the need to consider complex interactions for effective air pollution control and management in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Preharvest burning of sugarcane is a common agricultural practice in Florida, which produces fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤ 2.5 μ m ( PM 2.5 )] that is associated with higher mortality., Objectives: We estimated premature mortality associated with exposure to PM 2.5 from sugarcane burning in people age 25 y and above for 20 counties in South Florida., Methods: We combined information from an atmospheric dispersion model, satellites, and surface measurements to quantify PM 2.5 concentrations in South Florida and the fraction of PM 2.5 from sugarcane fires. From these concentrations, estimated mortalities attributable to PM 2.5 from sugarcane fires were calculated by census tract using health impact functions derived from literature for six causes of death linked to PM 2.5 . Confidence intervals (CI) are provided based on Monte Carlo simulations that propagate uncertainty in the emissions, dispersion model, health impact functions, and demographic data., Results: Sugarcane fires emitted an amount of primary PM 2.5 similar to that of motor vehicles in Florida. PM 2.5 from sugarcane fires is estimated to contribute to mortality rates within the Florida Sugarcane Growing Region (SGR) by 0.4 death per 100,000 people per year (95% CI: 0.3, 1.6 per 100,000). These estimates imply 2.5 deaths per year across South Florida were associated with PM 2.5 from sugarcane fires (95% CI: 1.2, 6.1), with 0.16 in the SGR (95% CI: 0.09, 0.6) and 0.72 in Palm Beach County (95% CI: 0.17, 2.2)., Discussion: PM 2.5 from sugarcane fires was estimated to contribute to mortality risk across South Florida, particularly in the SGR. This is consistent with prior studies that documented impacts of sugarcane fire on air quality but did not quantify mortality. Additional health impacts of sugarcane fires, which were not quantified here, include exacerbating nonfatal health conditions such as asthma and cardiovascular problems. Harvesting sugarcane without field burning would likely reduce PM 2.5 and health burdens in this region. https://doi.org/10.1289/EHP9957.

Fine particulate matter (PM 2.5 ) from U.S. anthropogenic sources is decreasing. However, previous studies have predicted that PM 2.5 emissions from wildfires will increase in the midcentury to next century, potentially offsetting improvements gained by continued reductions in anthropogenic emissions. Therefore, some regions could experience worse air quality, degraded visibility, and increases in population-level exposure. We use global climate model simulations to estimate the impacts of changing fire emissions on air quality, visibility, and premature deaths in the middle and late 21st century. We find that PM 2.5 concentrations will decrease overall in the contiguous United States (CONUS) due to decreasing anthropogenic emissions (total PM 2.5 decreases by 3% in Representative Concentration Pathway [RCP] 8.5 and 34% in RCP4.5 by 2100), but increasing fire-related PM 2.5 (fire-related PM 2.5 increases by 55% in RCP4.5 and 190% in RCP8.5 by 2100) offsets these benefits and causes increases in total PM 2.5 in some regions. We predict that the average visibility will improve across the CONUS, but fire-related PM 2.5 will reduce visibility on the worst days in western and southeastern U.S. regions. We estimate that the number of deaths attributable to total PM 2.5 will decrease in both the RCP4.5 and RCP8.5 scenarios (from 6% to 4-5%), but the absolute number of premature deaths attributable to fire-related PM 2.5 will double compared to early 21st century. We provide the first estimates of future smoke health and visibility impacts using a prognostic land-fire model. Our results suggest the importance of using realistic fire emissions in future air quality projections., (©2018. The Authors.)

Risks associated with exposure of individual plant species to ozone (O 3 ) are well documented, but implications for terrestrial biodiversity and ecosystem processes have received insufficient attention. This is an important gap because feedbacks to the atmosphere may change as future O 3 levels increase or decrease, depending on air quality and climate policies. Global simulation of O 3 using the Community Earth System Model (CESM) revealed that in 2000, about 40% of the Global 200 terrestrial ecoregions (ER) were exposed to O 3 above thresholds for ecological risks, with highest exposures in North America and Southern Europe, where there is field evidence of adverse effects of O 3 , and in central Asia. Experimental studies show that O 3 can adversely affect the growth and flowering of plants and alter species composition and richness, although some communities can be resilient. Additional effects include changes in water flux regulation, pollination efficiency, and plant pathogen development. Recent research is unraveling a range of effects belowground, including changes in soil invertebrates, plant litter quantity and quality, decomposition, and nutrient cycling and carbon pools. Changes are likely slow and may take decades to become detectable. CESM simulations for 2050 show that O 3 exposure under emission scenario RCP8.5 increases in all major biomes and that policies represented in scenario RCP4.5 do not lead to a general reduction in O 3 risks; rather, 50% of ERs still show an increase in exposure. Although a conceptual model is lacking to extrapolate documented effects to ERs with limited or no local information, and there is uncertainty about interactions with nitrogen input and climate change, the analysis suggests that in many ERs, O 3 risks will persist for biodiversity at different trophic levels, and for a range of ecosystem processes and feedbacks, which deserves more attention when assessing ecological implications of future atmospheric pollution and climate change.