Nutrient limitation is widespread among microbial decomposers of plant litter, as they often feed on substrates with much wider carbon (C)-to-nutrient ratios than those of their biomass. How they cope with nutrient (especially nitrogen, N) limitation remains an open question. Possible responses include: upregulating N acquisition; respiring excess C and thus lowering microbial C-use efficiency (CUE, ratio of C used for growth over C taken up); or retaining N more efficiently in microbial biomass growing in N-poor litter. We tested these hypotheses using a minimal model of litter decomposition that includes preferential N acquisition, CUE, and N recycling efficiency as parameters, resulting in alternative model variants. Parameters encoding microbial responses to N limitation were fitted to more than 500 litter decomposition curves, which trace how litter N changes as a function of litter C in individual litter cohorts. The model indicates that preferential N acquisition is upregulated at high litter C:N ratios, but the performance of model variants with flexible N acquisition was worse than that of the other variants, suggesting that microbes might respond to N limitation by regulating CUE or N recycling. CUE decreased with increasing litter C:N when N was not recycled from senescent biomass and N recycling efficiency increased with increasing litter C:N when CUE was fixed. Both these model variants (flexible CUE or N recycling efficiency) had high fitting performance. Moreover, flexible N recycling supported higher microbial growth rates compared to flexible CUE. These model results indicate that flexible N recycling can explain patterns in N import and release in litter, while also being a physiologically more beneficial response to cope with N limitation than regulation of CUE.
Uncertainty in estimations of the net contribution of anthropogenic aerosol particles, particularly of aerosol-cloud interactions (ACIs) to the Earth's radiation budget, limits our ability to understand past and project future climate change. Earth System Models (ESMs) are among the key tools for assessing the magnitude and impacts of changes in various forcing agents on the global climate system. Hence, improving aerosol and cloud descriptions in ESMs is an important way forward to increase the confidence in estimates of climate impacts of aerosol perturbations in the past, present and future. In the framework of the FORCeS project, experimental and theoretical approaches were combined to bridge the current key gaps in the fundamental understanding of essential aerosol and cloud processes and their descriptions in selected European ESMs. Regarding aerosol types and processes, we focused on organic aerosol, particulate nitrate, absorbing aerosols, and ultrafine aerosol sources including new particle formation and growth. In terms of cloud processes, we targeted cloud droplet activation, hydrometeor growth and evaporation, ice formation and multiplication as well as aerosol processing and scavenging by clouds. The selection was made based on the identified knowledge gaps in the scientific understanding of these processes and/or their current representation in ESMs, as well as a novel perturbed parameter ensemble approach to detecting potential structural deficiencies in an ESM. Here, we review the state-of-the-art, outline our approach for arriving at recommendations for improving the representation of key aerosol and cloud processes within ESMs, and then provide such recommendations applicable in models operating at the Earth system scale. The limitations of the recommendations, applicability, as well as alternative approaches and future research directions are discussed. Overall, the findings highlight the need for continuous efforts towards smart ways for representing the aerosol number size distribution as well as consistent representations of key parameters (e.g., liquid water content and cloud droplet number concentration). Furthermore, we provide guidance for future ESM evaluation emphasising, in particular, the need for exploring the consistency of key parameters, process-based (as opposed to parameter-based), and the complementarity of in-situ and remote-sensed measurements for model evaluation.
High-pressure blocking events are anticyclones that persist over a region for a long time. Such events prevent vertical mixing of air pollutants due to the subsidence inversion created by the anticyclone. This study investigates the relationship of aerosol concentrations during periods of high-pressure blocking events in southern Sweden for the rural location of Vavihill and the urban location of Malm & ouml;. A total of 226 highpressure blocking events were identified in Vavihill and Malm & ouml; between 1995 and 2024. The high-pressure blocking events were sorted according to wind direction, season, and average pressure for further analysis. Moreover, to determine whether the frequency of blocking events affecting the region is changing, meteorological data from southern Sweden between 1946 and 2024 was analysed. Using Mann-Kendall statistics and standard deviations, the data showed a significant increase of PM2.5 for both locations during periods of high-pressure blocking. The trend indicated an accumulation of aerosols during the event in both locations. The investigation showed a stronger increase in PM2.5 with winds from eastern and central Europe, indicating advective transport of aerosols to the region. Local emissions most likely also played a role in the increasing PM2.5 levels, as suggested by Malm & ouml; generally having higher aerosol concentrations than Vavihill. High-pressure blocking events with a mean pressure above 1026 hPa showed the strongest increase in PM2.5. No long-term increase in the frequency of high-pressure blocking events was found in the region. The results from this study show how aerosol concentrations and air quality are highly dependent on atmospheric events in the region.
Ammonia (NH3) is a central component of atmospheric reactive nitrogen, and a precursor gas that forms airborne particulate matter including nitrate and sulfate aerosol. Reducing ammonia emissions, primarily from agriculture, is a major challenge for air pollution mitigation and environmental protection. This work assesses the effects of ammonia emission reductions in Sweden, which is one of the EU Member States that are currently not meeting their emission reduction commitments. We apply the regional chemical transport model MATCH with improved NH3 treatment, and benchmark the updated model setup against surface observations of atmospheric NH3 and other nitrogen species for a large-scale model domain over Europe. We perform high-resolution regional simulations over Sweden, and compare the effects of reducing the emissions of (1) agricultural NH3, and (2) nitrogen oxides (NOx) from road transport, which is the second major nitrogen source in Sweden. The results show the potential of national NH3 emission reductions to mitigate NH3 levels, fine particulate matter (PM2.5) and nitrogen deposition within Sweden. While cutting NOx emissions is important for air pollution abatement through NOx mitigation, in Sweden the reductions have only minor or negligible effects on PM2.5 and nitrogen deposition. This demonstrates the benefits of NH3 reduction for both air quality and environment, and the impact of national abatement actions.
The changes in the concentration, distribution, and composition of anthropogenic aerosols impact cloud properties and cloud radiative effects. A distinct feature of the anthropogenic perturbation of aerosols is the hemispheric contrast, with much larger perturbations in the Northern Hemisphere. Observations of clouds in the two hemispheres, particularly alongside model simulations, may help constrain the magnitude of the effective radiativeforcing dueto aerosol-cloud interactions. This study investigates the impact of flipping the distribution of anthropogenic aerosol emissions between hemispheres on aerosol-cloud interactions using the aerosol-climate model ICON1.3.0-A-HAM2.3. It is shown, globally, that a clear, detectable, and attributable impact in aerosol optical depth results from anthropogenic emissions changes based on the counterpart hemisphere, an increase in the Southern Hemisphere, and a decrease in the Northern Hemisphere. The response to changes in anthropogenic aerosols in cloud droplet number concentration and liquid water path is particularly strong over land and is attributable using satellite data as a reference. Changes in enhanced/reduced aerosol emissions, through their interactions with radiation and clouds, produce a positive effective radiative forcing of 2.85 W m-2 in the Northern Hemisphere and a negative effective radiative forcing in the Southern Hemisphere of-2.63 W m-2.
Using model output from the Radiative Forcing Model Intercomparison Project (RFMIP), endorsed by the sixth Coupled Model Intercomparison Project 6 (CMIP6), we investigated the impact of aerosols on the Arctic climate (averaged over the region north of 66 degrees N) during winter. The average of these models shows that the presentday aerosols (as of the year 2014) result in a positive aerosol effective radiative forcing (ERFaer) of approximately 0.14 W m-2 in the Arctic during winter, relative to pre-industrial conditions defined as those of the year 1850. This positive ERFaer is associated with enhanced aerosol loading through strong transport from Eurasia and adjoining regions, causing the Arctic region to warm by up to 1 K in the present-day compared to the pre-industrial conditions. The Arctic warming attributed to aerosols also significantly affects climate variability, particularly the Arctic Oscillation (AO). Present-day aerosols resulted in a positively skewed distribution of the Arctic Oscillation index (AOI) compared to the control simulation, reflecting a shift toward more frequent positive AO phases associated with negative sea level pressure (SLP) anomalies across the northern Atlantic, Pacific, and Eurasian regions, and positive SLP anomalies over northern North America. Additionally, the transient experiment, which includes time-varying aerosol emissions, is used to investigate the sensitivity of Arctic winter climate to the aerosol enhancement, based on low and high aerosol scenarios. During the high aerosol scenario, warming in near-surface air temperature (SAT) is concentrated over the Arctic region, reaching approximately 1 K, while less warming is simulated in the low aerosol scenario. The AOI distribution is positively skewed in both aerosol scenarios, indicating that changes in aerosol concentrations influence the AO. However, the skewness is weaker under the high aerosol scenario compared to the low aerosol case, suggesting that stronger aerosol forcing tends to stabilize the AO and limit its variability. Nevertheless, increased sensitivity of the AO to aerosol can lead to extreme weather, particularly warmer winters in the Arctic, in contrast to most of the Northern Hemisphere, regardless of the AO phase. Our analysis also suggests that aerosol enhancement contributes to a shift in the jet stream's position. Furthermore, the lapse rate feedback (LRF), a contributor to the Arctic amplification, also shows an increase due to aerosol enhancement. This indicates that both the strength and magnitude of the LRF are sensitive to aerosol concentrations, which may further intensify Arctic warming/amplification.
Mobile, near-source measurements are broadly used for determining δ13CH4 of individual methane (CH4) emissions sources. To answer the need for robust and comparable measurement methods, we aim to define the best practices to determine isotopic signatures of CH4 sources from atmospheric measurements, considering instrument accuracy and precision. Using the Keeling and Miller-Tans methods, we verify the impact of linear fitting methods, averaging approaches, and for the Miller-Tans method, different background composition. Measurement techniques include Isotope Ratio Mass Spectrometry (IRMS) and Cavity Ring Down Spectroscopy (CRDS). The use of the active AirCore system for sampling, coupled to CRDS for measurement, is examined. Due to their higher precision and accuracy, the chosen data processing strategy does not significantly influence IRMS results. Comparatively lower-precision CRDS measurements are more sensitive to methodological choices. Fitting methods with forced symmetry like Major Axis or Bivariate Correlated Errors and Intrinsic Scatter (BCES) with orthogonal sub-method introduce significant bias in the determined δ13CH4 signatures using measurements from the lower-precision CRDS. The most reliable results are obtained for non-averaged data using fitting methods, which include uncertainties of x- and y-axis values, like York fitting or BCES (Y|X) sub-method, where x is treated as an independent variable. The Ordinary Least Squares method provides sufficiently robust results and can be used to determine δ13CH4 in near-source conditions. The present recommendations are aimed at laboratories measuring δ13CH4 source signatures to encourage consistency in the required methods for data analysis.
Studying primary biological aerosol particles in the Arctic is crucial to understanding their role in cloud formation and climate regulation at high latitudes. During the Arctic Ocean 2018 expedition, fluorescent primary biological aerosol particles (fPBAPs) were observed, using a multiparameter bioaerosol spectrometer, near the North Pole during the transition from summer to early fall. The fPBAPs showed a strong correlation with the occurrence of ice nucleating particles (INPs) and had similar concentration levels during the first half of the expedition. This relationship highlights the potential importance of biological sources of INPs in the formation of mixed-phase clouds during the central Arctic’s summer and early fall seasons. Our analysis shows that the observed fPBAPs were independent of local wind speed and the co-occurrence of other coarse mode particles, suggesting sources other than local sea spray from leads, melt ponds, re-suspension of particles from the surface, or other wind-driven processes within the pack ice. In contrast, other fluorescent particles were correlated with wind speed and coarse mode particle concentration. A multi-day event of high concentrations of fPBAPs was observed at the North Pole, during which the contribution of fPBAPs to the total concentration of coarse mode aerosol increased dramatically from less than 0.1% up to 55%. Analysis of chemical composition and particle size suggested a marine origin for these fPBAPs, a hypothesis further supported by additional evidence. Air parcel trajectory analysis coupled with ocean productivity reanalysis data, as well as analysis of large-scale meteorological conditions, all linked the high concentrations of fPBAPs to biologically active, ice-free areas of the Arctic Ocean.
Large-eddy simulation (LES) is often used as a benchmark simulation in climate science and is suggested as a fundamental tool to examine, e.g., marine cloud brightening. Therefore, it is necessary to critically evaluate if these high-resolution models can skillfully simulate expected physical phenomena. This study focuses on the first indirect aerosol effect in warm stratocumulus clouds. We investigate if an LES code with explicit aerosol-cloud interactions and a widely used two-moment bulk microphysical scheme can reproduce well-known cloud droplet number susceptibility regimes previously identified by observations and supported by detailed parcel model simulations—the updraft-limited regime (typically occurring at high aerosol number concentrations and low updraft speeds) and the aerosol-limited regime (typically occurring at low aerosol number concentrations and high updraft speeds). Our simulations show that the LES in its default configuration cannot reproduce the two regimes if the initial droplet radius of newly activated droplets (rid) is estimated by integrating the wet aerosol size distribution. The main reason is related to the relatively coarse (but commonly used) time step in the model (Δt ≈ 1s), which is too long to resolve relevant microphysical processes adequately at high aerosol concentrations. A regime transition does occur if the timestep is decreased to Δt ≈ 0.1s and if a renormalization procedure is applied, which limits the number of activated droplets so that the water mass of the newly activated droplets cannot exceed the available amount of supersaturated water vapor. Another way to obtain a regime transition is to increase rid to values >1 µm. However, a clear recommendation for the choice of rid cannot be made upon physical arguments. An alternative solution could be to introduce a sub-time-stepping or adaptive time-stepping algorithm to calculate droplet formation and growth, particularly for updraft-limited conditions. Our study highlights the importance of critically evaluating LES results to guarantee that relevant physical processes are properly represented.
We studied the influence of the Planetary Boundary Layer (PBL) on the air masses sampled at the mountaintop Hellenic Atmospheric Aerosol and Climate Change station ((HAC) 2 ) at Mount Helmos (Greece) during the Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISTHO) Campaign from September 2021 to March 2022. The PBL Height (PBLH) was determined from the standard deviation of the vertical wind velocity ( sigma w ) measured by a wind Doppler lidar (over a 30 -min time window with 30 m spatial resolution); the height for which sigma w drops below a characteristic threshold of 0.1 m s -1 corresponds to the PBLH. The air mass characterization is independently carried out using in situ measurements sampled at (HAC) 2 (equivalent black carbon, eBC ; fluorescent particle number, aerosol size distributions, absolute humidity). We found that a distinct diurnal cycle of aerosol properties is seen when the station is inside the PBL (i.e., PBLH exceeds the (HAC) 2 altitude); and a complete lack thereof when it is in the Free Tropospheric Layer (FTL). Additionally, we identified transition periods where the (HAC) 2 site location alternates between the FTL (usually during the early morning hours) and the PBL (usually during the midday and late afternoon hours), during which the concentration and characteristics of the aerosols vary the most. Transition periods are also when orographic clouds are formed. The highest PBLH values occur in September [400 m above (HAC) 2 ] followed by a transition period in November, while the lowest ones occur in January [200 m below (HAC) 2 ]. We found also that the PBLH increases by 16 m per 1 degrees C increase of the ground temperature.
Aerosol effects on cloud properties are notoriously difficult to disentangle from variations driven by meteorological factors. Here, a machine learning model is trained on reanalysis data and satellite retrievals to predict cloud microphysical properties, as a way to illustrate the relative importance of meteorology and aerosol, respectively, on cloud properties. It is found that cloud droplet effective radius can be predicted with some skill from only meteorological information, including estimated air mass origin and cloud top height. For ten geographical regions the mean coefficient of determination is 0.41 and normalised root-mean square error 24%. The machine learning model thereby performs better than a reference linear regression model, and a model predicting the climatological mean. A gradient boosting regression performs on par with a neural network regression model. Adding aerosol information as input to the model improves its skill somewhat, but the difference is small and the direction of the influence of changing aerosol burden on cloud droplet effective radius is not consistent across regions, and thereby also not always consistent with what is expected from cloud brightening.
Accurate quantification of air-sea gas transfer velocity is critical for our understanding of air-sea CO2 gas fluxes, global carbon budget and climate responses. CO2 transfer velocity is predominantly subject to constraints of wave-related dynamic processes at the ocean surface layer but is typically parameterized with wind speed. This study proposes and compares two parameterizations which accommodate dimensionless wave terms. The validations are conducted using both laboratory and field measurements of CO2 transfer and wave statistics. A scaling of bubble-mediated gas transfer is implemented into the formula that is linked to wave breaking probability. The improved parameterizations are capable of collapsing combined laboratory and field data sets which comprise diversified conditions of wind, wave and wave breaking.
This study used a water volume-based sampling method in combination with an active fog collector (modified Caltech design) to collect fog water samples during three intensive operation periods at two mountainous study sites in Taiwan. The new setup employed a sample-volume controlled system that dosed the fog water into 10 ml aliquots, which were then collected with a commercial laboratory auto-sampler. We collected fog water samples about 10 times more frequently (median sampling period 3 minutes and 45 seconds) than with traditional sampling schemes. Notably, up to over 200 samples were collected within a single fog event lasting 13 hours. The results showed that the intra-event variabilities of pH (up to over 2 units), conductivity (range almost 1000 μS cm–1), and ion concentrations were generally higher than the inter-event variability. The variabilities exhibited particularly fast changes during phases of fog onset and dissolution; in contrast, the centers of the passing clouds at our mountain research sites were rather homogeneous. Overall, our new method showed a marked improvement in sampling speed over traditional methods.
More than 40 years of aerosol data including concentrations of particle number and of nine major ions collected over the Southern Ocean and coastal stations have been aggregated and filtered with back trajectories to reduce the risk of influence from adjacent continents. That provided a rich dataset including latitudinal distribution and seasonality of physical and chemical aerosol parameters that allow insights into aerosol sources over the Southern Ocean. These data together with statistics of back trajectory paths of high (75% percentile) and low (25% percentile) concentrations of the studied aerosol parameters were used to identify potential source regions of the respective compounds. For particle number concentrations, MSA, and the non-sea-salt fractions of Ca and potassium the most prominent source regions were found in high DMS-areas close to Antarctica, whereas the potential source regions of NH4 and the non-sea-salt fraction of Mg were located in part further north over the Southern Ocean. These geographical differences would reflect differences in the marine biota.
Concurrent measurements of atmospheric O-2 and CO2 amount fractions have been used for decades now to estimate fluxes of carbon to and from the oceans and the land biosphere. The equations used in these estimates explicitly include fossil fuel combustion but are built on the assumption that fossil fuels are oxidized solely by atmospheric O-2, ignoring the small fraction of fossil fuel oxidation by oxide ores that occurs during refining of metals, and thereby overestimating losses of atmospheric O-2. Here, we address this deficiency by quantifying the effective O-2 fluxes associated with the processing of iron, aluminium and copper. We also consider the potential impact of sulfur. We find that consideration of the oxygen mobilized during metal processing (equivalent to a net O-2 flux of 12.0(-0.4)(+0.2) Tmol a(-1)) leads to an increased estimate of ocean carbon uptake in the years 2000-2010 of (0.144(-0.005)(+0.002))Pg a(-1) of carbon with a corresponding decrease in estimated land uptake. A rough estimate of oxygen uptake due to sulfur chemistry during fossil fuel combustion (2.4 Tmol a(-1)) decreases ocean carbon uptake but by a much smaller amount. These corrections are small compared to existing estimates of the fluxes and their uncertainties ((2.27 +/- 0.60) and (1.05 +/- 0.84) Pg a(-1) of carbon for ocean and land respectively (Keeling and Manning, 2014)) but should be employed in future analyses.
Two three-dimensional reanalysis datasets of atmospheric composition, the Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), are analyzed for the years 2003-2018 with respect to dust transport into the Arctic. The reanalyses agree on that the largest mass transport of dust into the Arctic occurs across western Russia during spring and early summer, but substantial transport events occasionally also occur across other geographical areas during all seasons. In many aspects, however, the reanalyses show considerable differences: the mass transport in MERRA-2 is substantially larger, more spread out, and occurs at higher altitudes than in CAMSRA, while the transport in CAMSRA is to a higher degree focused to well-defined events in space and time; the integrated mass transport of the 10 most intense 36-hour dust events in CAMSRA constitutes 6 % of the total integrated dust transport 2003-2018, whereas the corresponding value for MERRA-2 is only 1 %. Furthermore, we compare the reanalyses with surface measurements of dust in the Arctic and dust extinction retrievals from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite data. This comparison indicates that CAMSRA underestimates the dust transport into the Arctic and that MERRA-2 likely overestimates it. The discrepancy between CAMSRA and MERRA-2 can partially be explained by the assimilation process where too little dust is assimilated in CAMSRA while in MERRA-2, the assimilation process increases the dust concentration in remote areas. Despite the profound differences between the reanalyses regarding dust transport into the Arctic, this study still brings new insights into the spatio-temporal distribution of the transport. We estimate the annual dust transport into the Arctic to be within the range 1.5-31 Tg, where the comparison with observations indicates that the lower end of the interval is less likely.
Important aspects of the adjustments to aerosol-cloud interactions can be examined using the relationship between cloud droplet number concentration (Nd) and liquid water path (LWP). Specifically, this relation can constrain the role of aerosols in leading to thicker or thinner clouds in response to adjustment mechanisms. This study investigates the satellite retrieved relationship between Nd and LWP for a selected case of mid-latitude continental clouds using high-resolution Large-eddy simulations (LES) over a large domain in weather prediction mode. Since the satellite retrieval uses adiabatic assumption to derive the Nd (NAd), we have also considered NAd from the LES model for comparison. The NAd-LWP relationship in the satellite and the LES model show similar, generally positive, but non-monotonic relations. This case over continent thus behaves differently compared to previously-published analysis of oceanic clouds, and the analysis illustrates a regime dependency (marine and continental) in the NAd-LWP relation in the satellite retrievals. The study further explores the impact of the satellite retrieval assumptions on the Nd-LWP relationship. When considering the relationship of the actually simulated cloud-top Nd, rather than NAd, with LWP, the result shows a much more nonlinear relationship. The difference is much less pronounced, however, for shallow stratiform than for convective clouds. Comparing local vs large-scale statistics from satellite data shows that continental clouds exhibit only a weak nonlinear Nd-LWP relationship. Hence a regime based Nd-LWP analysis is even more relevant when it comes to continental clouds.
Storm-resolving simulations where deep convection can be explicitly resolved are performed in the idealized radiative-convective equilibrium framework to explore the climatic role of interactive leaf phenology. By initializing the system with different initial soil moisture and leaf area index (LAI) conditions, we find three categories of potential equilibrium climatic and vegetation states: a hot desert planet without vegetation, an intermediate sparsely vegetated planet, and a wet fully vegetated planet. The wet fully vegetated equilibrium category occurs over the widest range of initial soil moisture as it occurs as soon as soil saturation is 19% higher than the permanent wilting point (35%). This indicates that a quite harsh environment is needed in our modeling system to force leaves to be shed. The attained equilibrium states are only dependent upon the initial soil moisture, not the initial LAI. However, interactive leaves do allow an earlier transition from the intermediate to the wet vegetated equilibrium category. Hence, interactive leaves make the vegetation-atmosphere system more stable and more resilient to drying. This effect could be well approximated by just prescribing the LAI to its maximum value. Finally, our sensitivity experiments reveal that leaves influence the climate equally through their controls on canopy conductance and vegetation cover, whereas albedo changes play a negligible role.
This review presents how the boreal and the tropical forests affect the atmosphere, its chemical composition, its function, and further how that affects the climate and, in return, the ecosystems through feedback processes. Observations from key tower sites standing out due to their long-term comprehensive observations: The Amazon Tall Tower Observatory in Central Amazonia, the Zotino Tall Tower Observatory in Siberia, and the Station to Measure Ecosystem-Atmosphere Relations at Hyytiäla in Finland. The review is complemented by short-term observations from networks and large experiments. The review discusses atmospheric chemistry observations, aerosol formation and processing, physiochemical aerosol, and cloud condensation nuclei properties and finds surprising similarities and important differences in the two ecosystems. The aerosol concentrations and chemistry are similar, particularly concerning the main chemical components, both dominated by an organic fraction, while the boreal ecosystem has generally higher concentrations of inorganics, due to higher influence of long-range transported air pollution. The emissions of biogenic volatile organic compounds are dominated by isoprene and monoterpene in the tropical and boreal regions, respectively, being the main precursors of the organic aerosol fraction. Observations and modeling studies show that climate change and deforestation affect the ecosystems such that the carbon and hydrological cycles in Amazonia are changing to carbon neutrality and affect precipitation downwind. In Africa, the tropical forests are so far maintaining their carbon sink. It is urgent to better understand the interaction between these major ecosystems, the atmosphere, and climate, which calls for more observation sites, providing long-term data on water, carbon, and other biogeochemical cycles. This is essential in finding a sustainable balance between forest preservation and reforestation versus a potential increase in food production and biofuels, which are critical in maintaining ecosystem services and global climate stability. Reducing global warming and deforestation is vital for tropical forests.
Aerosol simulations especially for Earth System Models require a thermodynamics module with a good compromise between rigor and computational efficiency. We present and evaluate ISORROPIA-lite, an accelerated and simplified version of the widely used ISORROPIA-II v.2.3 aerosol thermodynamics model, expanded to include the effects of water uptake from organics and an updated interface communicating simulation diagnostics and information. ISORROPIA-lite assumes the aerosol is in metastable equilibrium (i.e., salts do not precipitate from supersaturated solutions) and treats the thermodynamics of Na+–NH4+–SO42––NO3––Cl––Ca2+–K+–Mg2+–Organics–H2O aerosol using binary activity coefficients from precalculated look-up tables. Off-line comparison between ISORROPIA-II and ISORROPIA-lite (without organic water effects) for more than 330,000 atmospherically-relevant states demonstrated that 'i') ISORROPIA-lite provides virtually identical results with ISORROPIA-II in metastable mode and 'ii') differences between stable mode ISORROPIA-II and ISORROPIA-lite are less than 25% for the concentrations of the various semivolatile aerosol components and similar to the differences between stable and metastable modes of ISORROPIA-II. Using ISORROPIA-lite reduced computational cost by 35% compared to ISORROPIA-II simulations in stable mode with online calculation of binary activity coefficients. Application of ISORROPIA-lite in the PMCAMx chemical transport model accelerated the 3D simulations by about 10% compared to using ISORROPIA-II in stable mode with changes in the concentrations of the major aerosol components of less than 10%. Simulations considering the effects of the organic aerosol water did not slow down ISORROPIA-lite but increased the concentrations of the inorganic semivolatile components especially at nighttime. Organic water could highly contribute to the total PM1 water mass and increase the concentrations of fine nitrate and ammonium by as much as 1 μg m–3 in places where the organic aerosol and RH levels are high.
