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Aerosol particles cool the climate by scattering solar radiation and by acting as cloud condensation nuclei. Higher temperatures resulting from increased greenhouse gas levels have been suggested to lead to increased biogenic secondary organic aerosol and cloud condensation nuclei concentrations creating a negative climate feedback mechanism. Here, we present direct observations on this feedback mechanism utilizing collocated long term aerosol chemical composition measurements and remote sensing observations on aerosol and cloud properties. Summer time organic aerosol loadings showed a clear increase with temperature, with simultaneous increase in cloud condensation nuclei concentration in a boreal forest environment. Remote sensing observations revealed a change in cloud properties with an increase in cloud reflectivity in concert with increasing organic aerosol loadings in the area. The results provide direct observational evidence on the significance of this negative climate feedback mechanism. Vegetation emits organic vapors which can form aerosols in the atmosphere and influence cloud properties. Here, the authors show observational evidence that warmer temperatures lead to increased emissions of these aerosols in boreal forests which cause surface cooling, demonstrating a negative climate feedback mechanism.

Boreal forests cover vast areas of land in the high latitudes of the Northern Hemisphere, which are under amplified climate warming. The interactions between the forests and the atmosphere are known to generate a complex set of feedback processes. One feedback process, potentially producing a cooling effect, is associated with an increased reflectance of clouds due to aerosol–cloud interactions. Here, we investigate the effect that the boreal forest environment can have on cloud-related properties during the growing season. The site investigated was the SMEAR II station in Hyytiälä, Finland. Air mass back trajectories were the basis of the analysis and were used to estimate the time each air mass had spent over land prior to its arrival at the station. This enabled tracking the changes occurring in originally marine air masses as they travelled across the forested land. Only air masses arriving from the northwestern sector were investigated, as these areas have a relatively uniform forest cover and relatively little anthropogenic interference. We connected the air mass analysis with comprehensive in situ and remote-sensing data sets covering up to 11 growing seasons. We found that the properties of air masses with short land transport times, thereby less influenced by the forest, differed from those exposed to the forest environment for a longer period. The fraction of air masses with cloud condensation nuclei concentrations (at 0.2 % supersaturation) above the median value of 180 cm−3 of the analysed air masses increased from approximately 10 % to 80 % after 55 h of exposure to boreal forest, while the fraction of air masses with specific humidity above the median value of 5 g kg−1 increased from roughly 25 % to 65 %. Signs of possible resulting changes in the cloud layer were also observed from satellite measurements. Lastly, precipitation frequency increased from the average of approximately 7 % to about 12 % after a threshold of 50 h of land transport. Most of the variables showed an increase with an increasing land transport time until approximately 50–55 h, after which a balance with little further variation seemed to have been reached. This appears to be the approximate timescale in which the forest–cloud interactions take effect and the air masses adjust to the local forest environment.

In the aqueous phase, fine particulate matter can form reactive species (RS) that influence the aging, properties, and health effects of atmospheric aerosols. In this study, we explore the RS yields of aerosol samples from a remote forest (Hyytiälä, Finland) and polluted urban locations (Mainz, Germany; Beijing, China), and we relate the RS yields to different chemical constituents and reaction mechanisms. Ultra-high-resolution mass spectrometry was used to characterize organic aerosol composition, electron paramagnetic resonance (EPR) spectroscopy with a spin-trapping technique was applied to determine the concentrations of ⚫OH, O2⚫-, and carbon- or oxygen-centered organic radicals, and a fluorometric assay was used to quantify H2O2. The aqueous H2O2-forming potential per mass unit of ambient PM2.5 (particle diameter < 2.5 µm) was roughly the same for all investigated samples, whereas the mass-specific yields of radicals were lower for sampling sites with higher concentrations of PM2.5. The abundances of water-soluble transition metals and aromatics in ambient PM2.5 were positively correlated with the relative fraction of ⚫OH and negatively correlated with the relative fraction of carbon-centered radicals. In contrast, highly oxygenated organic molecules (HOM) were positively correlated with the relative fraction of carbon-centered radicals and negatively correlated with the relative fraction of ⚫OH. Moreover, we found that the relative fractions of different types of radicals formed by ambient PM2.5 were comparable to surrogate mixtures comprising transition metal ions, organic hydroperoxide, H2O2, and humic or fulvic acids. The interplay of transition metal ions (e.g., iron and copper ions), highly oxidized organic molecules (e.g., hydroperoxides), and complexing or scavenging agents (e.g., humic or fulvic acids) leads to nonlinear concentration dependencies in aqueous-phase RS production. A strong dependence on chemical composition was also observed for the aqueous-phase radical yields of laboratory-generated secondary organic aerosols (SOA) from precursor mixtures of naphthalene and β-pinene. Our findings show how the composition of PM2.5 can influence the amount and nature of aqueous-phase RS, which may explain differences in the chemical reactivity and health effects of particulate matter in clean and polluted air.

Particulate black carbon (BC) affects global warming by absorbing the solar radiation, by affecting cloud formation, and by decreasing ground albedo when deposited to snow or ice. BC has also a wide variety of adverse effects on human population health. In this article we reviewed the BC emission factors (EFs) of major anthropogenic sources, i.e. traffic (incl. marine and aviation), residential combustion, and energy production. We included BC EFs measured directly from individual sources and EFs derived from ambient measurements. Each source category was divided into sub-categories to find and demonstrate systematical trends, such as the potential influence of fuel, combustion technologies, and exhaust/flue gas cleaning systems on BC EFs. Our review highlights the importance of society level emission regulation in BC emission mitigation; a clear BC emission reduction was observed in ambient studies for road traffic as well as in direct emission measurements of diesel-powered individual vehicles. However, the BC emissions of gasoline vehicles were observed to be higher for vehicles with direct fuel injection techniques (gasoline direct injection) than for vehicles with port-fueled injection, indicating potentially negative trend in gasoline vehicle fleet BC EFs. In the case of shipping, a relatively clear correlation was seen between the engine size and BC EFs so that the fuel specific BC EFs of the largest engines were the lowest. Regarding the BC EFs from residential combustion, we observed large variation in EFs, indicating that fuel type and quality as well as combustion appliances significantly influence BC EFs. The largest data gaps were in EFs of large-scale energy production which can be seen crucial for estimating global radiative forcing potential of anthropogenic BC emissions. In addition, much more research is needed to improve global coverage of BC EFs. Furthermore, the use of existing data is complicated by different EF calculation methods, different units used in reporting and by variation of results due to different experimental setups and BC measurement methods. In general, the conducted review of BC EFs is seen to significantly improve the accuracy of future emission inventories and the evaluations of the climate, air quality, and health impacts of anthropogenic BC emissions.

Soil is a major contributor to the biosphere–atmosphere exchange of carbonyl sulfide (COS) and carbon monoxide (CO). COS is a tracer with which to quantify terrestrial photosynthesis based on the coupled leaf uptake of COS and CO2, but such use requires separating soil COS flux, which is unrelated to photosynthesis, from ecosystem COS uptake. For CO, soil is a significant natural sink that influences the tropospheric CO budget. In the boreal forest, magnitudes and variabilities of soil COS and CO fluxes remain poorly understood. We measured hourly soil fluxes of COS, CO, and CO2 over the 2015 late growing season (July to November) in a Scots pine forest in Hyytiälä, Finland. The soil acted as a net sink of COS and CO, with average uptake rates around 3 pmol m−2 s−1 for COS and 1 nmol m−2 s−1 for CO. Soil respiration showed seasonal dynamics controlled by soil temperature, peaking at around 4 µmol m−2 s−1 in late August and September and dropping to 1–2 µmol m−2 s−1 in October. In contrast, seasonal variations of COS and CO fluxes were weak and mainly driven by soil moisture changes through diffusion limitation. COS and CO fluxes did not appear to respond to temperature variation, although they both correlated well with soil respiration in specific temperature bins. However, COS : CO2 and CO : CO2 flux ratios increased with temperature, suggesting possible shifts in active COS- and CO-consuming microbial groups. Our results show that soil COS and CO fluxes do not have strong variations over the late growing season in this boreal forest and can be represented with the fluxes during the photosynthetically most active period. Well-characterized and relatively invariant soil COS fluxes strengthen the case for using COS as a photosynthetic tracer in boreal forests.

Catalytic materials of alumina and lanthana supported nanosized palladium particles (7 wt%) in a water suspension were prepared by Liquid Flame Spray (LFS) method. The particle production rate was 90 g/h, using liquid precursors containing Al(NO3)3 · 9H2O, La(NO3)3 · 6H2O and Pd(NH3)4NO3 in water solution. In the LFS method, a turbulent, high-temperature (Tmax ∼ 2,700 °C) H2–O2 flame is used. The liquid precursor is atomized into micron sized droplets by high velocity H2 flow and introduced into the flame where the droplets will evaporate. The evaporated compounds decompose and the reaction product re-condenses into particulate material. Here, the nanosized particles are formed by gas-to-particle conversion and the micron sized particles via liquid-to-solid route. In this study, the produced particulate material was collected by thermophoresis along with condensing water into a suspension (nanoparticles in water) in a one-step process. Thus, the whole suspension was produced from the end products of the flame. According to TEM-EDS analysis, the particulate material contained micron sized porous aluminum oxide or lanthanum oxide carrier particles, coated by nanosized palladium particles (∼2–10 nm). The surfactant (Rhodasurf-La 42) was injected into the suspension just after collection to reduce agglomeration. Catalytic performance of the produced Pd–lanthana containing suspension was tested in laboratory with synthetic gases, in order to use it as a possible raw material for three-way catalyst (TWC). The suspension was used as Pd raw material in TWC washcoat and dispersed onto a metallic honeycomb.

The Station for Measuring Ecosystem–Atmosphere Relations (SMEAR) II is well known among atmospheric scientists due to the immense amount of observational data it provides of the Earth–atmosphere interface. Moreover, SMEAR II plays an important role for the large European research infrastructure, enabling the large scientific community to tackle climate- and air-pollution-related questions, utilizing the high-quality long-term data sets recorded at the site. So far, this well-documented site was missing the description of the seasonal variation in aerosol chemical composition, which helps understanding the complex biogeochemical and physical processes governing the forest ecosystem. Here, we report the sub-micrometer aerosol chemical composition and its variability, employing data measured between 2012 and 2018 using an Aerosol Chemical Speciation Monitor (ACSM). We observed a bimodal seasonal trend in the sub-micrometer aerosol concentration culminating in February (2.7, 1.6, and 5.1 µg m−3 for the median, 25th, and 75th percentiles, respectively) and July (4.2, 2.2, and 5.7 µg m−3 for the median, 25th, and 75th percentiles, respectively). The wintertime maximum was linked to an enhanced presence of inorganic aerosol species (ca. 50 %), whereas the summertime maximum (ca. 80 % organics) was linked to biogenic secondary organic aerosol (SOA) formation. During the exceptionally hot months of July of 2014 and 2018, the organic aerosol concentrations were up to 70 % higher than the 7-year July mean. The projected increase in heat wave frequency over Finland will most likely influence the loading and chemical composition of aerosol particles in the future. Our findings suggest strong influence of meteorological conditions such as radiation, ambient temperature, and wind speed and direction on aerosol chemical composition. To our understanding, this is the longest time series reported describing the aerosol chemical composition measured online in the boreal region, but the continuous monitoring will also be maintained in the future.

The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol–cloud interactions within warm clouds. Long-term CCN number concentration (NCCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating NCCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between NCCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ångström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (σsp) of PM10 particles. The analysis first showed that the dependence of NCCN on supersaturation (SS) can be described by a logarithmic fit in the range SS <1.1 %, without any theoretical reasoning. The relationship between NCCN and AOPs was parameterized as NCCN≈((286±46)SAE ln(SS/(0.093±0.006))(BSF − BSFmin) + (5.2±3.3))σsp, where BSFmin is the minimum BSF, in practice the 1st percentile of BSF data at a site to be analyzed. At the lowest supersaturations of each site (SS ≈0.1 %), the average bias, defined as the ratio of the AOP-derived and measured NCCN, varied from ∼0.7 to ∼1.9 at most sites except at a Himalayan site where the bias was >4. At SS >0.4 % the average bias ranged from ∼0.7 to ∼1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, ∼1.4–1.9. In other words, at SS >0.4 % NCCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ångström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured NCCN varied from ∼0.5 to ∼0.8. To study the physical explanation of the relationships between NCCN and AOPs, lognormal unimodal particle size distributions were generated and NCCN and AOPs were calculated. The simulation showed that the relationships of NCCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of NCCN and AOPs were similar to those of the observed ones.

The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol-cloud interactions within warm clouds. Long-term CCN number concentration (N.sub.CCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating N.sub.CCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between N.sub.CCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ãngström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (Ï.sub.sp) of PM.sub.10 particles. The analysis first showed that the dependence of N.sub.CCN on supersaturation (SS) can be described by a logarithmic fit in the range SS <1.1 %, without any theoretical reasoning. The relationship between N.sub.CCN and AOPs was parameterized as NCCNâ((286±46)SAE ln(SS/(0.093±0.006))(BSF - BSF.sub.min) + (5.2±3.3))Ï.sub.sp, where BSF.sub.min is the minimum BSF, in practice the 1st percentile of BSF data at a site to be analyzed. At the lowest supersaturations of each site (SS â0.1 %), the average bias, defined as the ratio of the AOP-derived and measured N.sub.CCN, varied from â¼0.7 to â¼1.9 at most sites except at a Himalayan site where the bias was 4. At SS 0.4 % the average bias ranged from â¼0.7 to â¼1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, â¼1.4-1.9. In other words, at SS 0.4 % N.sub.CCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ãngström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured N.sub.CCN varied from â¼0.5 to â¼0.8. To study the physical explanation of the relationships between N.sub.CCN and AOPs, lognormal unimodal particle size distributions were generated and N.sub.CCN and AOPs were calculated. The simulation showed that the relationships of N.sub.CCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of N.sub.CCN and AOPs were similar to those of the observed ones.

New particle formation driven by acid–base chemistry was initiated in the CLOUD chamber at CERN by introducing atmospherically relevant levels of gas-phase sulfuric acid and dimethylamine (DMA). Ammonia was also present in the chamber as a gas-phase contaminant from earlier experiments. The composition of particles with volume median diameters (VMDs) as small as 10 nm was measured by the Thermal Desorption Chemical Ionization Mass Spectrometer (TDCIMS). Particulate ammonium-to-dimethylaminium ratios were higher than the gas-phase ammonia-to-DMA ratios, suggesting preferential uptake of ammonia over DMA for the collected 10–30 nm VMD particles. This behavior is not consistent with present nanoparticle physicochemical models, which predict a higher dimethylaminium fraction when NH3 and DMA are present at similar gas-phase concentrations. Despite the presence in the gas phase of at least 100 times higher base concentrations than sulfuric acid, the recently formed particles always had measured base : acid ratios lower than 1 : 1. The lowest base fractions were found in particles below 15 nm VMD, with a strong size-dependent composition gradient. The reasons for the very acidic composition remain uncertain, but a plausible explanation is that the particles did not reach thermodynamic equilibrium with respect to the bases due to rapid heterogeneous conversion of SO2 to sulfate. These results indicate that sulfuric acid does not require stabilization by ammonium or dimethylaminium as acid–base pairs in particles as small as 10 nm.