| 1. |
- Beal, Jacob, et al.
(författare)
-
Robust estimation of bacterial cell count from optical density
- 2020
-
Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
-
Tidskriftsartikel (refereegranskat)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
|
|
| 2. |
- Abazajian, Kevork, et al.
(författare)
-
CMB-S4 : Forecasting Constraints on Primordial Gravitational Waves
- 2022
-
Ingår i: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 926:1
-
Tidskriftsartikel (refereegranskat)abstract
- CMB-S4—the next-generation ground-based cosmic microwave background (CMB) experiment—is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the universe. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semianalytic projection tool, targeted explicitly toward optimizing constraints on the tensor-to-scalar ratio, r, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2–3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments, given a desired scientific goal. To form a closed-loop process, we couple this semianalytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for r > 0.003 at greater than 5σ, or in the absence of a detection, of reaching an upper limit of r < 0.001 at 95% CL.
|
|
| 3. |
- Kanai, M, et al.
(författare)
-
- 2023
-
swepub:Mat__t
|
|
| 4. |
- Niemi, MEK, et al.
(författare)
-
- 2021
-
swepub:Mat__t
|
|
| 5. |
- Blichner, Sara M., 1989-, et al.
(författare)
-
Process-evaluation of forest aerosol-cloud-climate feedback shows clear evidence from observations and large uncertainty in models
- 2024
-
Ingår i: Nature Communications. - 2041-1723. ; 15
-
Tidskriftsartikel (refereegranskat)abstract
- Natural aerosol feedbacks are expected to become more important in the future, as anthropogenic aerosol emissions decrease due to air quality policy. One such feedback is initiated by the increase in biogenic volatile organic compound (BVOC) emissions with higher temperatures, leading to higher secondary organic aerosol (SOA) production and a cooling of the surface via impacts on cloud radiative properties. Motivated by the considerable spread in feedback strength in Earth System Models (ESMs), we here use two long-term observational datasets from boreal and tropical forests, together with satellite data, for a process-based evaluation of the BVOC-aerosol-cloud feedback in four ESMs. The model evaluation shows that the weakest modelled feedback estimates can likely be excluded, but highlights compensating errors making it difficult to draw conclusions of the strongest estimates. Overall, the method of evaluating along process chains shows promise in pin-pointing sources of uncertainty and constraining modelled aerosol feedbacks.
|
|
| 6. |
- Isokääntä, Sini, et al.
(författare)
-
The effect of clouds and precipitation on the aerosol concentrations and composition in a boreal forest environment
- 2022
-
Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 22:17, s. 11823-11843
-
Tidskriftsartikel (refereegranskat)abstract
- Atmospheric aerosol particle concentrations are strongly affected by various wet processes, including below and in-cloud wet scavenging and in-cloud aqueous-phase oxidation. We studied how wet scavenging and cloud processes affect particle concentrations and composition during transport to a rural boreal forest site in northern Europe. For this investigation, we employed air mass history analysis and observational data. Long-term particle number size distribution (∼15 years) and composition measurements (∼8 years) were combined with air mass trajectories with relevant variables from reanalysis data. Some such variables were rainfall rate, relative humidity, and mixing layer height. Additional observational datasets, such as temperature and trace gases, helped further evaluate wet processes along trajectories with mixed effects models.All chemical species investigated (sulfate, black carbon, and organics) exponentially decreased in particle mass concentration as a function of accumulated precipitation along the air mass route. In sulfate (SO4) aerosols, clear seasonal differences in wet removal emerged, whereas organics (Org) and equivalent black carbon (eBC) exhibited only minor differences. The removal efficiency varied slightly among the different reanalysis datasets (ERA-Interim and Global Data Assimilation System; GDAS) used for the trajectory calculations due to the difference in the average occurrence of precipitation events along the air mass trajectories between the reanalysis datasets.Aqueous-phase processes were investigated by using a proxy for air masses travelling inside clouds. We compared air masses with no experience of approximated in-cloud conditions or precipitation during the past 24 h to air masses recently inside non-precipitating clouds before they entered SMEAR II (Station for Measuring Ecosystem–Atmosphere Relations). Significant increases in SO4 mass concentration were observed for the latter air masses (recently experienced non-precipitating clouds).Our mixed effects model considered other contributing factors affecting particle mass concentrations in SMEAR II: examples were trace gases, local meteorology, and diurnal variation. This model also indicated in-cloud SO4 production. Despite the reanalysis dataset used in the trajectory calculations, aqueous-phase SO4 formation was observed. Particle number size distribution measurements revealed that most of the in-cloud SO4 formed can be attributed to particle sizes larger than 200 nm (electrical mobility diameter). Aqueous-phase secondary organic aerosol (aqSOA) formation was non-significant.
|
|
| 7. |
- Karlsson, Linn, et al.
(författare)
-
Physical and Chemical Properties of Cloud Droplet Residuals and Aerosol Particles During the Arctic Ocean 2018 Expedition
- 2022
-
Ingår i: Journal of Geophysical Research - Atmospheres. - 2169-897X .- 2169-8996. ; 127:11
-
Tidskriftsartikel (refereegranskat)abstract
- Detailed knowledge of the physical and chemical properties and sources of particles that form clouds is especially important in pristine areas like the Arctic, where particle concentrations are often low and observations are sparse. Here, we present in situ cloud and aerosol measurements from the central Arctic Ocean in August–September 2018 combined with air parcel source analysis. We provide direct experimental evidence that Aitken mode particles (particles with diameters ≲70 nm) significantly contribute to cloud condensation nuclei (CCN) or cloud droplet residuals, especially after the freeze-up of the sea ice in the transition toward fall. These Aitken mode particles were associated with air that spent more time over the pack ice, while size distributions dominated by accumulation mode particles (particles with diameters ≳70 nm) showed a stronger contribution of oceanic air and slightly different source regions. This was accompanied by changes in the average chemical composition of the accumulation mode aerosol with an increased relative contribution of organic material toward fall. Addition of aerosol mass due to aqueous-phase chemistry during in-cloud processing was probably small over the pack ice given the fact that we observed very similar particle size distributions in both the whole-air and cloud droplet residual data. These aerosol–cloud interaction observations provide valuable insight into the origin and physical and chemical properties of CCN over the pristine central Arctic Ocean.
|
|
| 8. |
- Lowe, Samuel Joseph, 1991-
(författare)
-
Modelling the effects of organic aerosol phase partitioning processes on cloud formation
- 2020
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Atmospheric aerosols particles may act as cloud condensation nuclei (CCN) that provide sites for condensation of water vapour for the formation of cloud droplets, called cloud droplet activation. Whether aerosol particles are CCN is determined by their size, composition and the ambient humidity. Cloud macrophysical properties together with the size and number concentration of droplets determine the optical properties of liquid phase clouds. Clouds are an important component in the Earth's radiation balance and aerosol-cloud interactions (ACI) are associated with the largest uncertainty in estimates made of anthropogenic radiative forcing in earth system models.To constrain ACI and reduce uncertainties, an improvement in our understanding of CCN activation is required. Owing to its complex phase structure and chemical heterogeneity, the organic fraction of atmospheric aerosol introduces significant challenges in developing an exact description of cloud formation. In this thesis, a cloud parcel model is employed to systematically address parametric and process uncertainties in estimates of cloud droplet sizes and number concentrations (CDNC). To do so, the unified framework for organic aerosol (UFO) scheme was developed and embedded into the cloud parcel model, ICPM-UFO. The ICPM-UFO simulates partitioning of organic mass between the gas and aqueous bulk and surface phases, thereby providing means to theoretically diagnose changes in droplet nucleating potential of aerosol particles due to organic aerosol mass transfer processes.Partitioning of surface active organic aerosol mass from the bulk particle phase to the surface phase results in a lowered, size-dependent surface tension that enhances activation potential of CCN and therefore simulated CDNC. A large fraction of organic aerosol constituents exist partitioned across particle and gas phases and simulation of cloud formation events show this semi-volatile organic mass to condense to the particle phase as humidity increases through the cloud base. This additional particle phase mass may be partially soluble. The more soluble component increases the activation potential by lowering the water activity, while the less soluble but more surface active component also increases the activation potential by further lowering of the surface tension. The compounding effects of the gas-particle and bulk-surface partitioning processes result in significant changes in CCN concentrations and CDNC for simulation on boreal aerosol. These results exhibit a significant over prediction of typical boreal CCN concentrations relative to in-situ measurements, though further sensitivity analysis with respect to the soluble fraction and surface phase description may be advantageous. Based on multivariate statistical approaches applied, resolution of the surface phase in cloud formation parameterisations within climate models is however not currently recommended.Theoretical description of both partitioning processes require prescription of input parameters that are challenging to measure in-situ. These parameters include: SVOC volatility and enthalpy of vaporisation and organic component surface tension and film thickness. Further work using the inverse modelling framework established herein is recommended to provide estimation of these parameters while simultaneously matching simulated CDNC and/or CCN concentrations with observational data. It is envisaged that such an investigation will also yield insights into structural uncertainties associated with the choice of surface phase model - a point of contention both within this thesis and the wider literature.
|
|
