• Other research productsclose
• Open Access close
• Academy of Finland close
• European Commission close
• EU close
• JP close
• English close

This repository contains the relevant data and code supporting the study "An ancestral molecular response to nanomaterial particulates" (DOI: 10.1038/s41565-023-01393-4). In detail the following data sources have been included: - the preprocessed transcriptomic datasets GSE157266 and GSE148705 included in the discovery set (curated_transcriptomic_data.zip); - supplementary materials of the paper, including curated molecular descriptors panels and the ENM gene signature (supplementary_files.zip); -The preprocessed microarray transcriptomics data for drug exposure have been curated from a selection of the Open Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (TG-GATEs) data (transcriptomic_data_drug_exposures.zip); -the chemical signatures collected from the Comparative Toxicogenomics Database (CTD) (CTD_signatures.zip); -the list of dose dependent genes for individual transcriptomic dataset (dose_dependent_genes.zip); -the relevant code and input data (code.zip and input_data.zip)

The data is from a mesocosm experiment set up outside Lima, Peru to study the influence of upwelling of oxygen minimum zone (OMZ) water. The mesocosm bags were 2 m in diameter and extended from the surface down to 19 m depth, where the last 2 m was a conical sediment trap. Eight mesocosm bags were used and they were moored at 12.0555°S; 77.2348°W just north of Isla San Lorenzo where the water depth is ~30 m. The experiment was started 25 February 2017 by closing the mesocosm bags and were run for 50 days. Two treatments were used (water with different OMZ signature), each with four replicates. Water (100 m3) from the OMZ was collected from two locations and depths. The first was collected from 12.028323°S; 77.223603°W from 30 m depth, and the second one from 12.044333°S; 77.377583°W from 70 m depth. The original aim was to collect severe and moderate OMZ signature water (differing in e.g. nitrate concentrations) from the first and second site, respectively. This assumption was based on long-term monitoring data, however, the chemical properties (e.g. nitrate concentration) was more similar in these water masses than anticipated, rather reflecting low and very low OMZ signatures from site 1 and 2 respectively. To have a baseline of measured variables, the mesocosms where closed and environmental and biological variables were determined over 10 days. After this period, the OMZ water was added to the mesocosms in two steps on day 11 and 12 after the enclosure of the mesocosms. As the mesocosms contain a specific volume (~54 m3), the process of adding the OMZ water started with first removing water from the mesocosms. The water removed (~20 m3) was pumped out from 11-12 m depth. A similar volume of OMZ water, from both collection sites, was then pumped into four replicate mesocosms each. The OMZ water was pumped into the mesocosms moving the input hose between 14-17 m depth. The water collected at 30 m depth was pumped into mesocosms M1, M4, M5 and M8 having a low OMZ signature and water from 70 m depth into mesocosms M2, M3, M6 and M7 having a very low OMZ signature. Due a halocline at 12 m depth (see below), the added OMZ water was not immediately mixed throughout the mesocosm bag. Sampling took place every second day over a period of 50 days, and all variables were taken with an integrated water sampler (HydroBios, IWS) pre-programed to fill from 0 – 10 m depth and all samples consisted of this integrated samples from the upper 10 m. The samples were stored dark in cool boxes and brought back to the laboratory and processed right away. Sampling took place in the morning, and the samples were usually back in the laboratory around noon. Measured variables included inorganic nutrients, dissolved organic nutrients, extracellular enzyme activity: leucine aminopeptidase (LAP) and alkaline phosphatase, and the phytoplankton and bacterial community composition.

Solid state coolers based on superconducting tunnel junctions are promising low temperature cooling devices which are routinely fabricated using modern microfabrication methods. Arising applications from quantum technologies often depend on subKelvin temperature to operate, requiring the use of bulky and expensive dilution refrigerators. Solid state coolers can potentially replace dilution refrigerators by cascading several microcoolers operating in different temperature ranges. In order to achieve this, coolers have to be packed efficiently, thus 3D integration is essential. In this thesis, vertical integration of superconducting solid state coolers is studied and developed. Flip-chip bonding is utilized to interconnect two microchips together. Samples are studied before and after bonding, and the thermal resistance of 3D integrated device is determined. Quality assurance of the process focuses on indium bumps and isolation etching of adjacent islands in the cooler device. Cooling is notobserved in the device, as the flaws in the isolation etching limit the full capability of the device. However, thermal response of a device is studied, finding that the thermal resistance is significantly improved compared to previous work.

In the present-day atmosphere, sulfuric acid is the most important vapour for aerosol particle formation and initial growth. However, the growth rates of nanoparticles (<10 nm) from sulfuric acid remain poorly measured. Therefore, the effect of stabilizing bases, the contribution of ions and the impact of attractive forces on molecular collisions are under debate. Here, we present precise growth rate measurements of uncharged sulfuric acid particles from 1.8 to 10 nm, performed under atmospheric conditions in the CERN (European Organization for Nuclear Research) CLOUD chamber. Our results show that the evaporation of sulfuric acid particles above 2 nm is negligible, and growth proceeds kinetically even at low ammonia concentrations. The experimental growth rates exceed the hard-sphere kinetic limit for the condensation of sulfuric acid. We demonstrate that this results from van der Waals forces between the vapour molecules and particles and disentangle it from charge–dipole interactions. The magnitude of the enhancement depends on the assumed particle hydration and collision kinetics but is increasingly important at smaller sizes, resulting in a steep rise in the observed growth rates with decreasing size. Including the experimental results in a global model, we find that the enhanced growth rate of sulfuric acid particles increases the predicted particle number concentrations in the upper free troposphere by more than 50 %.

The paper presents a comparative study of age of air (AoA) derived from several approaches: a widely used passive-tracer accumulation method, the SF6 accumulation, and a direct calculation of an ideal-age tracer. The simulations were performed with the Eulerian chemistry transport model SILAM driven with the ERA-Interim reanalysis for 1980–2018. The Eulerian environment allowed for simultaneous application of several approaches within the same simulation and interpretation of the obtained differences. A series of sensitivity simulations revealed the role of the vertical profile of turbulent diffusion in the stratosphere, destruction of SF6 in the mesosphere, and the effect of gravitational separation of gases with strongly different molar masses. The simulations reproduced well the main features of the SF6 distribution in the atmosphere observed by the MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) satellite instrument. It was shown that the apparent very old air in the upper stratosphere derived from the SF6 profile observations is a result of destruction and gravitational separation of this gas in the upper stratosphere and the mesosphere. These processes make the apparent SF6 AoA in the stratosphere several years older than the ideal-age AoA, which, according to our calculations, does not exceed 6–6.5 years. The destruction of SF6 and the varying rate of emission make SF6 unsuitable for reliably deriving AoA or its trends. However, observations of SF6 provide a very useful dataset for validation of the stratospheric circulation in a model with the properly implemented SF6 loss.

Recent studies have shown the importance of new particle formation (NPF) to global cloud condensation nuclei (CCN) production, as well as to air pollution in megacities. In addition to the necessary presence of low-volatility vapors that can form new aerosol particles, both numerical and observational studies have shown that the dynamics of the planetary boundary layer (BL) plays an important role in NPF. Evidence from field observations suggests that roll vortices might be favorable for inducing NPF in a convective BL. However, direct observations and estimates of the potential importance of this phenomenon to the production of new aerosol particles are lacking. Here we show that rolls frequently induce NPF bursts along the horizontal circulations and that the small clusters and particles originating from these localized bursts grow in size similar to particles typically ascribed to atmospheric NPF that occur almost homogeneously at a regional scale. We outline a method to identify roll-induced NPF from measurements and, based on the collected data, estimate the impact of roll vortices on the overall aerosol particle production due to NPF at a boreal forest site (83 % ± 34 % and 26 % ± 8 % overall enhancement in particle formation for 3 and 10 nm particles, respectively). We conclude that the formation of roll vortices should be taken into account when estimating particle number budgets in the atmospheric BL.

We present a case study where emission metric values from different studies are applied to estimate global and Arctic temperature impacts of emissions from a northern European country. This study assesses the climate impact of Finnish air pollutants and greenhouse gas emissions from 2000 to 2010, as well as future emissions until 2030. We consider both emission pulses and emission scenarios. The pollutants included are SO2, NOx, NH3, non-methane volatile organic compound (NMVOC), black carbon (BC), organic carbon (OC), CO, CO2, CH4 and N2O, and our study is the first one for Finland to include all of them in one coherent dataset. These pollutants have different atmospheric lifetimes and influence the climate differently; hence, we look at different climate metrics and time horizons. The study uses the global warming potential (GWP and GWP*), the global temperature change potential (GTP) and the regional temperature change potential (RTP) with different timescales for estimating the climate impacts by species and sectors globally and in the Arctic. We compare the climate impacts of emissions occurring in winter and summer. This assessment is an example of how the climate impact of emissions from small countries and sources can be estimated, as it is challenging to use climate models to study the climate effect of national policies in a multi-pollutant situation. Our methods are applicable to other countries and regions and present a practical tool to analyze the climate impacts in multiple dimensions, such as assessing different sectors and mitigation measures. While our study focuses on short-lived climate forcers, we found that the CO2 emissions have the most significant climate impact, and the significance increases over longer time horizons. In the short term, emissions of especially CH4 and BC played an important role as well. The warming impact of BC emissions is enhanced during winter. Many metric choices are available, but our findings hold for most choices.

Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm−3 in bare soil and lichen tundra and 89 g dm−3 in other LCTs. Total moss biomass varied from 0 to 820 g m−2, total vascular shoot mass from 7 to 112 g m−2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 ∘C in bare soil and lichen tundra, and varied from 5 to 9 ∘C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14–34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6–15 % of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models.

Freshwaters bring a notable contribution to the global carbon budget by emitting both carbon dioxide (CO2) and methane (CH4) to the atmosphere. Global estimates of freshwater emissions traditionally use a wind-speed-based gas transfer velocity, kCC (introduced by Cole and Caraco, 1998), for calculating diffusive flux with the boundary layer method (BLM). We compared CH4 and CO2 fluxes from BLM with kCC and two other gas transfer velocities (kTE and kHE), which include the effects of water-side cooling to the gas transfer besides shear-induced turbulence, with simultaneous eddy covariance (EC) and floating chamber (FC) fluxes during a 16-day measurement campaign in September 2014 at Lake Kuivajärvi in Finland. The measurements included both lake stratification and water column mixing periods. Results show that BLM fluxes were mainly lower than EC, with the more recent model kTE giving the best fit with EC fluxes, whereas FC measurements resulted in higher fluxes than simultaneous EC measurements. We highly recommend using up-to-date gas transfer models, instead of kCC, for better flux estimates. BLM CO2 flux measurements had clear differences between daytime and night-time fluxes with all gas transfer models during both stratified and mixing periods, whereas EC measurements did not show a diurnal behaviour in CO2 flux. CH4 flux had higher values in daytime than night-time during lake mixing period according to EC measurements, with highest fluxes detected just before sunset. In addition, we found clear differences in daytime and night-time concentration difference between the air and surface water for both CH4 and CO2. This might lead to biased flux estimates, if only daytime values are used in BLM upscaling and flux measurements in general. FC measurements did not detect spatial variation in either CH4 or CO2 flux over Lake Kuivajärvi. EC measurements, on the other hand, did not show any spatial variation in CH4 fluxes but did show a clear difference between CO2 fluxes from shallower and deeper areas. We highlight that while all flux measurement methods have their pros and cons, it is important to carefully think about the chosen method and measurement interval, as well as their effects on the resulting flux.