The rapidly warming Arctic undergoes transitions that can influence global carbon balance. One of the key processes is the shift towards vegetation types with higher biomass underlining a stronger carbon sink. The shift is predicted by bioclimatic models based on abiotic climatic factors, but it is not always confirmed with observations. Recent studies highlight the role of disturbances in the shift. Here we use high-resolution remote sensing to study the process of transition from tundra to forest and its connection to wildfires in the 20 000  km 2 area in northwest Siberia. Overall, 40  % of the study area was burned during a 60-year period. Three-quarters of the burned areas were dry tundra. About 10  % of the study area experienced two–three fires with an interval of 15–60 years suggesting a shorter fire return interval than that reported earlier for the northern areas of central Siberia (130–350 years). Based on our results, the shift in vegetation (within the 60-year period) occurred in 40 %–85 % of the burned territories. All fire-affected territories were flat; therefore no effect of topography was detected. Oppositely, in the undisturbed areas, a transition of vegetation was observed only in 6 %–15 % of the territories, characterized by steeper topographic slopes. Our results suggest a strong role of disturbances in the tree advance in northwest Siberia.

In air quality research, often only size-integrated particle mass concentrations as indicators of aerosol particles are considered. However, the mass concentrations do not provide sufficient information to convey the full story of fractionated size distribution, in which the particles of different diameters ( D p ) are able to deposit differently on respiratory system and cause various harm. Aerosol size distribution measurements rely on a variety of techniques to classify the aerosol size and measure the size distribution. From the raw data the ambient size distribution is determined utilising a suite of inversion algorithms. However, the inversion problem is quite often ill-posed and challenging to solve. Due to the instrumental insufficiency and inversion limitations, imputation methods for fractionated particle size distribution are of great significance to fill the missing gaps or negative values. The study at hand involves a merged particle size distribution, from a scanning mobility particle sizer (NanoSMPS) and an optical particle sizer (OPS) covering the aerosol size distributions from 0.01 to 0.42  µm (electrical mobility equivalent size) and 0.3 to 10  µm (optical equivalent size) and meteorological parameters collected at an urban background region in Amman, Jordan, in the period of 1 August 2016–31 July 2017. We develop and evaluate feed-forward neural network (FFNN) approaches to estimate number concentrations at particular size bin with (1) meteorological parameters, (2) number concentration at other size bins and (3) both of the above as input variables. Two layers with 10–15 neurons are found to be the optimal option. Worse performance is observed at the lower edge ( 0.01 D p 0.02   µm ), the mid-range region ( 0.15 D p 0.5   µm ) and the upper edge ( 6 D p 10   µm ). For the edges at both ends, the number of neighbouring size bins is limited, and the detection efficiency by the corresponding instruments is lower compared to the other size bins. A distinct performance drop over the overlapping mid-range region is due to the deficiency of a merging algorithm. Another plausible reason for the poorer performance for finer particles is that they are more effectively removed from the atmosphere compared to the coarser particles so that the relationships between the input variables and the small particles are more dynamic. An observable overestimation is also found in the early morning for ultrafine particles followed by a distinct underestimation before midday. In the winter, due to a possible sensor drift and interference artefacts, the estimation performance is not as good as the other seasons. The FFNN approach by meteorological parameters using 5 min data ( R 2 =  0.22–0.58) shows poorer results than data with longer time resolution ( R 2 =  0.66–0.77). The FFNN approach using the number concentration at the other size bins can serve as an alternative way to replace negative numbers in the size distribution raw dataset thanks to its high accuracy and reliability ( R 2 =  0.97–1). This negative-number filling approach can maintain a symmetric distribution of errors and complement the existing ill-posed built-in algorithm in particle sizer instruments.

The occurrence frequency of regional atmospheric new aerosol particle formation and consecutive growth events ( f NPF ) were studied with respect to vegetation activity, aerosol properties, air pollutants and meteorological data in Budapest over the time interval from 2008 to 2018. The data set evaluated contained results of in situ measurements on the land surface that were mostly performed at the Budapest platform for Aerosol Research and Training Laboratory, of satellite-based products recorded by MODIS on Terra and of modelled vegetation emission-related properties from an advanced regional biogeochemical model. The annual mean relative occurrence frequencies were considerable (with an overall mean of 21 %), remained at a constant level (with an overall SD of 5 %) and did not exhibit tendentious change over the years. The shape of the distributions of monthly mean f NPF exhibited large variability from year to year, while the overall average distribution already possessed a characteristic pattern. The structure of the new particle formation (NPF) occurrence distributions was compared to those of environmental variables including concentrations of gas-phase H 2 SO 4 , SO 2 , O 3 , NO, NO 2 , CO, PM 10 mass and NH 3 ; particle numbers in the size fractions of 6–1000, 6–100 and 100–1000  nm ; condensation sink; air temperature ( T ); relative humidity (RH); wind speed (WS); atmospheric pressure ( P ); global solar radiation (GRad); gross primary production (GPP) of vegetation; leaf area index (LAI); and stomatal conductance (SCT). There were no evident systematic similarities between f NPF on the one hand and all of the variables studied on the other hand, except for H 2 SO 4 and perhaps NH 3 . The spring maximum in the NPF occurrence frequency distribution often overlapped with the time intervals of positive  T anomaly in vegetated territories. The link between the potential heat stress exerted on plants in sultry summer intervals and the summer f NPF minimum could not be proven. The relevance of environmental variables was assessed by their ratios on NPF event days and on non-event days. The gas-phase H 2 SO 4 concentration showed the largest monthly ratios, followed by O 3 . The WS, biogenic precursor gases and SO 2 can generally favour NPF events, although their influence seemed to be constrained. An association between the f NPF and vegetation growth dynamics was clearly identified.

Ice-nucleating particles (INPs) trigger the formation of cloud ice crystals in the atmosphere. Therefore, they strongly influence cloud microphysical and optical properties and precipitation and the life cycle of clouds. Improving weather forecasting and climate projection requires an appropriate formulation of atmospheric INP concentrations. This remains challenging as the global INP distribution and variability depend on a variety of aerosol types and sources, and neither their short-term variability nor their long-term seasonal cycles are well covered by continuous measurements. Here, we provide the first year-long set of observations with a pronounced INP seasonal cycle in a boreal forest environment. Besides the observed seasonal cycle in INP concentrations with a minimum in wintertime and maxima in early and late summer, we also provide indications for a seasonal variation in the prevalent INP type. We show that the seasonal dependency of INP concentrations and prevalent INP types is most likely driven by the abundance of biogenic aerosol. As current parameterizations do not reproduce this variability, we suggest a new mechanistic description for boreal forest environments which considers the seasonal variation in INP concentrations. For this, we use the ambient air temperature measured close to the ground at 4.2 m height as a proxy for the season, which appears to affect the source strength of biogenic emissions and, thus, the INP abundance over the boreal forest. Furthermore, we provide new INP parameterizations based on the Ice Nucleation Active Surface Site (INAS) approach, which specifically describes the ice nucleation activity of boreal aerosols particles prevalent in different seasons. Our results characterize the boreal forest as an important but variable INP source and provide new perspectives to describe these new findings in atmospheric models.

Despite the numerous studies investigating haze formation mechanism in China, it is still puzzling that intensive haze episodes could form within hours directly following relatively clean periods. Haze has been suggested to be initiated by the variation of meteorological parameters and then to be substantially enhanced by aerosol–radiation–boundary layer feedback. However, knowledge on the detailed chemical processes and the driving factors for extensive aerosol mass accumulation during the feedback is still scarce. Here, the dependency of the aerosol number size distribution, mass concentration and chemical composition on the daytime mixing layer height (MLH) in urban Beijing is investigated. The size distribution and chemical composition-resolved dry aerosol light extinction is also explored. The results indicate that the aerosol mass concentration and fraction of nitrate increased dramatically when the MLH decreased from high to low conditions, corresponding to relatively clean and polluted conditions, respectively. Particles having their dry diameters in the size of ∼400 –700  nm , and especially particle-phase ammonium nitrate and liquid water, contributed greatly to visibility degradation during the winter haze periods. The dependency of aerosol composition on the MLH revealed that ammonium nitrate and aerosol water content increased the most during low MLH conditions, which may have further triggered enhanced formation of sulfate and organic aerosol via heterogeneous reactions. As a result, more sulfate, nitrate and water-soluble organics were formed, leading to an enhanced water uptake ability and increased light extinction by the aerosols. The results of this study contribute towards a more detailed understanding of the aerosol–chemistry–radiation–boundary layer feedback that is likely to be responsible for explosive aerosol mass growth events in urban Beijing.

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, O 2 • - , and carbon- or oxygen-centered organic radicals, and a fluorometric assay was used to quantify H 2 O 2 . The aqueous H 2 O 2 -forming potential per mass unit of ambient PM 2.5 (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 PM 2.5 . The abundances of water-soluble transition metals and aromatics in ambient PM 2.5 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 PM 2.5 were comparable to surrogate mixtures comprising transition metal ions, organic hydroperoxide, H 2 O 2 , 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 PM 2.5 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.