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.
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.
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.
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.
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.
Aerosols are a critical component of the climate system and a risk to human health. Here, the lockdown response to the coronavirus outbreak is used to analyse effects of dramatic reduction in anthropogenic aerosol sources on satellite-retrieved aerosol optical depth (AOD). A machine learning model is applied to estimate daily AOD during the initial lockdown in China in early 2020. The model uses information on aerosol climatology, geography and meteorological conditions, and explains 69% of the day-to-day AOD variability. A comparison of model-expected and observed AOD shows that no clear, systematic decrease in AOD is apparent during the lockdown in China. During March 2020, regional AOD is observed to be significantly lower than expected by the machine learning model in some coastal regions of the North China Plains and extending to the Korean peninsula. While this may possibly indicate a small lockdown effect on regional AOD, and potentially pointing trans-boundary effects of the lockdown measures, due to uncertainties associated with the method and the limited sample sizes, this AOD decrease cannot be unequivocally attributed to reduced anthropogenic emissions. Climatologically expected AOD is compared to a weather-adjusted expectation of AOD, indicating that meteorological influences have acted to significantly increase AOD during this time, in agreement with recent literature. The findings highlight the complexity of aerosol variability and the challenges of observation-based attribution of columnar aerosol changes.
Temperature inversions inhibit the transfer of momentum, heat and moisture in the atmosphere and have led to severe air pollution in China. This study investigated the spatiotemporal variation in temperature inversions in China using sounding data for the past four decades. Surface-based inversion, elevated inversion, and both in one sounding dataset were analysed. Statistical analyses of inversion parameters included frequency, strength and depth. The annual frequency of total inversions showed no significant increasing or decreasing trend with mean values of 0.78, 0.33, 0.24, 0.28, 0.5 and 0.36 at six stations representing different climate zones—Beijing, Harbin, Haikou, Shaowu, Ruoqiang, and Xining, respectively. The annual inversion strength and depth showed downward trends. Monthly variation in inversion frequency and strength differed among stations. The weakest surface-based inversion was found in summer at Beijing and Harbin with mean values of 1 and 1.3 °C, respectively; the strongest surface-based inversion was found in winter with respective mean values of 3.5 and 3.6 °C. Higher surface temperature in summer and subsidence aloft in winter may explain the monthly variation in inversion depth with a minimum in summer, with mean values of 165, 334, 135, 267, 363 and 420 m, and a maximum in winter, with mean values of 250, 646, 140, 591, 806 and 664 m, at the six respective stations. Total inversion was least frequent in southwestern China (mean 0.15), surface-based inversion was most frequent in the north (mean 0.78), and elevated inversion was most frequent in the southeast (mean 0.42). The strongest, deepest surface-based inversion dominated in the north (mean 3.4 °C and 398 m). Elevated inversion strength did not significantly differ among regions (mean 2.5 °C). The deepest elevated inversion dominated in the southeast (mean 654 m). Future efforts should focus on the interactions between aerosols and temperature inversions and accurate model simulations of temperature inversions.
The aim of this study was to explore particle size dependent properties by combining long-term observations of equivalent black carbon (eBC) and number size distributions to investigate their correlation as function of particle size. The work was conducted in two main parts. The first part consisted of a short laboratory experiment to compare observed total particle light absorption (σabs) with that observed according to particle size by using a combination of a Differential Mobility Analyzer (DMA) and a Particle Soot Absorption Photometer (PSAP). The laboratory study confirmed strong similarities between the observed and derived σabs. In the second part the statistical approach using correlation between the σabs and the dN of each bin of the number size distribution was tested on long-term data ranging from 2002 to 2010 observed at Zeppelin station, Ny-Ålesund Svalbard. The data was clustered according to the number size distribution and grouped in four major categories: Washout, Nucleation, Intermediate and Polluted. Each category presented different features with respect to the derived eBC mass distributions, the Intermediate category showed similarities to the few available Single Particle Soot Photometer (SP2) observations in the Arctic. Overall, the statistical distribution of eBC, according to particle size, presented a larger dynamical range in the location of the mode(s). To check for consistency, the eBC mass distributions were transformed into number based eBC size distribution and compared to the observed total number size distribution. Whereas the Washout, Nucleation and Intermediate categories presented plausible number distributions, the Polluted category displayed a mode at small sizes (about 50 nm) that was significantly exaggerated.
Extensive studies are available that analyse time series of carbon dioxide and water flux measurements of FLUXNET sites over many years and link these results to climate change such as changes in atmospheric carbon dioxide concentration, air temperature and growing season length and other factors. Many of the sites show trends to a larger carbon uptake. Here we analyse time series of net ecosystem exchange, gross primary production, respiration, and evapotranspiration of four forest sites with particularly long measurement periods of about 20 years. The regular trends shown are interrupted by periods with higher or lower increases of carbon uptake. These breakpoints can be of very different origin and include forest decline, increased vegetation period, drought effects, heat waves, and changes in site heterogeneity. The influence of such breakpoints should be included in long-term studies of land-atmosphere exchange processes.
With the rapid development of industry and economy, the problem of ozone (O3) pollution in China is of increasing concern in recent years. The problem of ozone pollution has become worse in Baicheng City which belongs to the province of Jilin. We analyze the spatial and temporal distribution of surface ozone and its correlation with precursors and meteorological factors during 2015 and 2019 using data from the automatic Atmospheric Environmental Quality Monitoring Station located in Baicheng. Results showed that the daily and monthly mean values of O3 concentration were both single-peak patterns, and interannual variation presented a inverted ‘V’ pattern in Baicheng. The high concentration of O3 in a year generally occurs from May to July, with the highest daily concentration occurring in the afternoon. The total number of days with O3 concentration exceeding the limits was 35 days from 2015 to 2019, among which the number of days exceeding the maximal daily average eight-hour (MDA8) O3 of 100 μg/m3 was the highest in 2018, and the 90th percentile MDA8 showed an overall growth pattern. Seasonal variations in O3 concentration in 2018 and 2019 were not consistent with the three previous years.
Total column ozone (TCO) monitoring with the Dobson spectrophotometer no. 84 have been carried out at Belsk (51°50′, 20°47′), Poland, since 23 March 1963. TCO observations were made for various combinations of double wavelength pairs (AD, CD, CC′) and instrument settings (direct Sun, zenith blue, and zenith cloudy). In total, results of 115,736 manual observations were recorded in the period 1963–2019. The following metrics of the intraday TCO variability are examined: standard deviation divided by the mean value and the difference between the daily maximum and minimum divided by the mean value. The mean value, standard deviation, and 5th–95th percentile range for the intraday changes of the metrics are {1.6%, 0.8%, 2.5%} and {4.3%, 2.3%, 7.3%,}, respectively. To examine interday TCO variability, one-day changes of the metrics and the daily mean TCO are analysed. The corresponding statistics for one-day change of TCO are {−0.2%, 6.9%, 22.6%}. The short-term TCO variability changed only slightly (if ever) since the beginning of the ozone observations at Belsk.
Deep convective clouds can transport trace gases from the planetary boundary layer into the upper troposphere where subsequent chemistry may impact aerosol particle formation and growth. In this modelling study, we investigate processes that affect isoprene and its oxidation products injected into the upper troposphere by an isolated deep convective cloud in the Amazon. We run a photochemical box model with coupled cloud microphysics along hundreds of individual air parcel trajectories sampled from a cloud-resolving model simulation of a convective event. The box model simulates gas-phase chemical reactions, gas scavenging by liquid and ice hydrometeors, and turbulent dilution inside a deep convective cloud. The results illustrate the potential importance of gas uptake to anvil ice in regulating the intensity of the isoprene oxidation and associated low volatility organic vapour concentrations in the outflow. Isoprene transport and fate also depends on the abundance of lightning-generated nitrogen oxide radicals (NOx = NO + NO2). If gas uptake on ice is efficient and lightning activity is low, around 30% of the boundary layer isoprene will survive to the cloud outflow after approximately one hour of transport, while all the low volatile oxidation products will be scavenged by the cloud hydrometeors. If lightning NOx is abundant and gas uptake by ice is inefficient, then all isoprene will be oxidised during transport or in the immediate outflow region, while several low volatility isoprene oxidation products will have elevated concentrations in the cloud outflow. Reducing uncertainties associated with the uptake of vapours on ice hydrometeors, especially HO2 and oxygenated organics, is essential to improve predictions of isoprene and its oxidation products in deep convective outflows and their potential contribution to new particle formation and growth.
