scholarly journals Intercomparison of thermal–optical carbon measurements by Sunset and Desert Research Institute (DRI) analyzers using the IMPROVE_A protocol

2021 ◽  
Vol 14 (5) ◽  
pp. 3217-3231
Author(s):  
Xiaolu Zhang ◽  
Krystyna Trzepla ◽  
Warren White ◽  
Sean Raffuse ◽  
Nicole Pauly Hyslop
Keyword(s):  
Atmospheric Aerosols ◽  
Dynamic Range ◽  
Optical Measurement ◽  
Model Performance ◽  
Total Carbon ◽  
Model Uncertainties ◽  
Model Transition ◽  
High Degree ◽  
Desert Research ◽  
Research Institute

Abstract. Thermal–optical analysis (TOA) is a class of methods widely used for determining organic carbon (OC) and elemental carbon (EC) in atmospheric aerosols collected on filters. Results from TOA vary not only with differences in operating protocols for the analysis, but also with details of the instrumentation with which a given protocol is carried out. Three models of TOA carbon analyzers have been used for the IMPROVE_A protocol in the past decade within the Chemical Speciation Network (CSN). This study presents results from intercomparisons of these three analyzer models using two sets of CSN quartz filter samples, all analyzed using the IMPROVE_A protocol with reflectance charring correction. One comparison was between the Sunset model 5L (Sunset) analyzers and the Desert Research Institute (DRI) model 2015 (DRI-2015) analyzers using 4073 CSN samples collected in 2017. The other comparison was between the Sunset and the DRI model 2001 (DRI-2001) analyzers using 303 CSN samples collected in 2007. Both comparisons showed a high degree of inter-model consistency in total carbon (TC) and the major carbon fractions, OC and EC, with a mean bias within 5 % for TC and OC and within 12 % for EC. Relatively larger and diverse inter-model discrepancies (mean biases of 5 %–140 %) were found for thermal subfractions of OC and EC (i.e., OC1–OC4 and EC1–EC3), with better agreement observed for subfractions with higher mass loadings and smaller within-model uncertainties. Optical charring correction proved critical in bringing OC and EC measurements by different TOA analyzer models into agreement. Appreciable inter-model differences in EC between Sunset and DRI-2015 (mean bias ±SD of 21.7 %±12.2 %) remained for ∼5 % of the 2017 CSN samples; examination of these analysis thermograms revealed that the optical measurement (i.e., filter reflectance and transmittance) saturated in the presence of strong absorbing materials on the filter (e.g., EC), leaving an insufficient dynamic range for the detection of carbon pyrolysis and thus no optical charring correction. Differences in instrument parameters and configuration, possibly related to disagreement in OC and EC subfractions, are also discussed. Our results provide a basis for future studies of uncertainties associated with the TOA analyzer model transition in assessing long-term trends of CSN carbon data. Further investigations using these data are warranted, focusing on the demonstrated inter-model differences in OC and EC subfractions. The within- and inter-model uncertainties are useful for model performance evaluation.

scholarly journals Inter-Comparison of Thermal-Optical Carbon Measurements by Sunset and DRI Analyzers Using the IMPROVE_A Protocol

2020 ◽  
Author(s):  
Xiaolu Zhang ◽  
Krystyna Trzepla ◽  
Warren White ◽  
Sean Raffuse ◽  
Nicole Pauly Hyslop
Keyword(s):  
Atmospheric Aerosols ◽  
Dynamic Range ◽  
Optical Measurement ◽  
Model Performance ◽  
Total Carbon ◽  
Monitoring Networks ◽  
Model Uncertainties ◽  
Model Transition ◽  
High Degree

Abstract. Thermal-Optical Analysis (TOA) is a class of methods widely used by long-term air quality monitoring networks for determining organic carbon (OC) and elemental carbon (EC) in atmospheric aerosols collected on filters. Results from TOA vary not only with differences in operating protocols for the analysis, but also with details of the instrumentation with which a given protocol is carried out. Three models of TOA carbon analyzers have been used for the IMPROVE_A protocol in the past decade within the Chemical Speciation Network (CSN). This study presents results from inter-comparisons of these three analyzer models using two sets of CSN quartz filter samples, all analyzed with the IMPROVE_A protocol. One comparison was between the Sunset Model 5L (Sunset) analyzers and the Desert Research Institute (DRI) Model 2015 (DRI-2015) analyzers, using 4073 CSN samples collected in 2017. The other comparison was between the Sunset and the DRI Model 2001 (DRI-2001) analyzers, using 303 CSN samples collected in 2007. Both comparisons showed a high degree of inter-model consistency in total carbon (TC) and the major carbon fractions, OC and EC, with mean bias within 5 % for TC and OC, and within 12 % for EC. Relatively larger and diverse inter-model differences (mean biases of 5 %–140 %) were found for thermal subfractions of OC and EC (i.e. OC1-OC4 and EC1-EC3), with better agreement observed for subfractions with higher mass loadings and smaller within-model uncertainties. Optical charring correction was found to be critical in bringing OC and EC measurements by different TOA analyzer models into better agreement. Appreciable inter-model differences in EC between Sunset and DRI-2015 (mean bias ± SD of 21.7 % ± 12.2 %) remained for ~ 5 % of the 2017 CSN samples; examination of these analysis thermograms revealed that the optical measurement (i.e. filter reflectance and transmittance) saturated in the presence of strong absorbing materials on the filter (e.g. EC), with excessive absorption leaving insufficient dynamic range for detection of carbon pyrolysis, thus no optical charring correction. Differences in possible instrument parameters and configuration related to disagreement in OC and EC subfractions are also discussed. Our results provide a basis for future studies of uncertainties associated with the TOA analyzer model transition in assessing long-term trends of CSN carbon data. Further investigations using these data are warranted focusing on the demonstrated inter-model differences in OC and EC subfractions. The within- and inter- model uncertainties are useful for model performance evaluation.

scholarly journals Atmospheric aging of small-scale wood combustion emissions (model MECHA 1.0) – is it possible to distinguish causal effects from non-causal associations?

2020 ◽  
Author(s):  
Ville Leinonen ◽  
Petri Tiitta ◽  
Olli Sippula ◽  
Hendryk Czech ◽  
Ari Leskinen ◽  
...  
Keyword(s):  
Atmospheric Aerosols ◽  
Model Performance ◽  
Equation System ◽  
Small Scale ◽  
Atmospheric Conditions ◽  
Wood Combustion ◽  
Emission Data ◽  
Atmospheric Aging ◽  
Causal Pathway ◽  
Pass Through

Abstract. Primary emissions of wood combustion are complex mixtures of hundreds or even over a thousand compounds, which pass through a series of chemical reactions and physical transformation processes in the atmosphere (aging). This aging process depends on atmospheric conditions, such as concentration of atmospheric oxidizing agents (OH radical, ozone and nitrate radicals), humidity and solar radiation, and is known to strongly affect the characteristics of atmospheric aerosols. However, there are only few models that are able to represent the aging of emissions during its lifetime in the atmosphere. In this work, we implemented a model (Model for aging of Emissions in environmental CHAmber, MECHA v 1.0) to describe the evolution by differential equation system. The model performance was first evaluated using two different, simulated datasets. The purpose of the evaluation was to investigate the ability of the model to (1) find the correct relationships between the variables in the dataset and (2) to evaluate the accuracy of the model to reproduce the evolution of variables in time. Subsequently, the model was implemented to wood combustion exhaust in atmosphere, based on a dataset from smog chamber experiments. Evaluation in simulated datasets served as a basis of the drawings made from modeled aging of the residential wood combustion emission. We found that the model was able to reproduce the evolution of the variables in time reasonably well. By using the state of the art detection algorithms for causal structures, we could unveil a large number of relationships for measured variables. However, as the emission data is complex in its nature due to multiple processes interacting with each other, for many relationships it was not possible to say if there was a causal pathway or if the variables were just covarying. This study serves as the first step towards a comprehensive model for the description of the evolution of the whole emission in both gas- and particle phase during atmospheric aging. We present contributions to challenges faced in this kind of modeling and discuss the possible improvements and expected importance of those for the model.

AMS 14C and Chemical Composition of Atmospheric Aerosols from Mexico City

Radiocarbon ◽  
2017 ◽  
Vol 59 (2) ◽  
pp. 321-332 ◽  
Author(s):  
C Solís ◽  
V Gómez ◽  
E Ortíz ◽  
E Chávez ◽  
J Miranda ◽  
...  
Keyword(s):  
Mexico City ◽  
Atmospheric Aerosols ◽  
Material Balance ◽  
Total Carbon ◽  
Crustal Material ◽  
Carbonaceous Matter ◽  
Mineral Salts ◽  
Fossil Carbon ◽  
Biogenic Carbon ◽  
The City

AbstractAir pollution in Mexico City, which has more than 22 million inhabitants, continues to be one of the main environmental issues. Aerosol samples (PM10) collected in Mexico City and the city of Cuernavaca (a clean reference site) have been characterized using different techniques. This multifaceted approach addresses the source apportionment of the carbonaceous matter in PM10, as well as the airborne elements and ions. Accelerator mass spectrometry (AMS) radiocarbon analysis of total carbon, X-ray fluorescence (XRF), and ion chromatography were performed on aerosols collected at three sites in Mexico City and one site in Cuernavaca, during 2 months of the cold-dry season (November–December) in 2012. New results obtained for Mexico City are compared with previous reports. Average levels of PM10 were higher in Mexico City sites (43.3–60.8 μg/m3) than in Cuernavaca (32.2 μg/m3). According to the material balance, PM10 collected in Mexico City had a lower contribution of crustal material (31.2–36.8%) than Cuernavaca (46.9%). Average contributions of particulate carbonaceous matter to PM10 were similar in both cities, but much higher contributions of mineral salts, trace elements, and ions were observed in Mexico City in comparison to Cuernavaca. Total organic carbon (OC) and elemental carbon (EC) contents were higher in aerosols from Mexico City than those from Cuernavaca. The temporal variation results showed that within all locations studied the OC concentration was high compared to the EC. Results from a theoretical calculation of fossil carbon (FC) and biogenic carbon (BC) concentrations showed that FC and BC levels depend on the site: at Mexico City sites, FC was equal or higher than BC. At Cuernavaca, BC was always higher than FC.

scholarly journals Software Polarization Spectrometer "PolariS"

2014 ◽  
Vol 03 (03n04) ◽  
pp. 1450010 ◽  
Author(s):  
Izumi Mizuno ◽  
Seiji Kameno ◽  
Amane Kano ◽  
Makoto Kuroo ◽  
Fumitaka Nakamura ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Graphics Processing Unit ◽  
Zeeman Splitting ◽  
High Spectral Resolution ◽  
Processing Unit ◽  
Analog To Digital ◽  
Star Forming ◽  
Device Architecture ◽  
Graphics Processing ◽  
High Degree

We have developed a software-based polarization spectrometer, PolariS, to acquire full-Stokes spectra with a very high spectral resolution of 61 Hz. The primary aim of PolariS is to measure the magnetic fields in dense star-forming cores by detecting the Zeeman splitting of molecular emission lines. The spectrometer consists of a commercially available digital sampler and a Linux computer. The computer is equipped with a graphics processing unit (GPU) to process FFT and cross-correlation using the Compute Unified Device Architecture (CUDA) library developed by NVIDIA. Thanks to a high degree of precision in quantization of the analog-to-digital converter and arithmetic in the GPU, PolariS offers excellent performances in linearity, dynamic range, sensitivity, bandpass flatness and stability. The software has been released under the MIT License and is available to the public. In this paper, we report the design of PolariS and its performance verified through engineering tests and commissioning observations.

Desert Research Institute: A Formula for Growth

Science ◽  
1968 ◽  
Vol 161 (3844) ◽  
pp. 866-869 ◽  
Author(s):  
P. M. Boffey
Keyword(s):  
Desert Research ◽  
Research Institute

scholarly journals Simple Deterministically Constructed Cycle Reservoirs with Regular Jumps

2012 ◽  
Vol 24 (7) ◽  
pp. 1822-1852 ◽  
Author(s):  
Ali Rodan ◽  
Peter Tiňo
Keyword(s):  
State Space ◽  
Unit Disk ◽  
Short Term Memory ◽  
Model Performance ◽  
Memory Capacity ◽  
Eigenvalue Distribution ◽  
Superior Performance ◽  
Reservoir Models ◽  
Linear Reservoir ◽  
High Degree

A new class of state-space models, reservoir models, with a fixed state transition structure (the “reservoir”) and an adaptable readout from the state space, has recently emerged as a way for time series processing and modeling. Echo state network (ESN) is one of the simplest, yet powerful, reservoir models. ESN models are generally constructed in a randomized manner. In our previous study (Rodan & Tiňo, 2011 ), we showed that a very simple, cyclic, deterministically generated reservoir can yield performance competitive with standard ESN. In this contribution, we extend our previous study in three aspects. First, we introduce a novel simple deterministic reservoir model, cycle reservoir with jumps (CRJ), with highly constrained weight values, that has superior performance to standard ESN on a variety of temporal tasks of different origin and characteristics. Second, we elaborate on the possible link between reservoir characterizations, such as eigenvalue distribution of the reservoir matrix or pseudo-Lyapunov exponent of the input-driven reservoir dynamics, and the model performance. It has been suggested that a uniform coverage of the unit disk by such eigenvalues can lead to superior model performance. We show that despite highly constrained eigenvalue distribution, CRJ consistently outperforms ESN (which has much more uniform eigenvalue coverage of the unit disk). Also, unlike in the case of ESN, pseudo-Lyapunov exponents of the selected optimal CRJ models are consistently negative. Third, we present a new framework for determining the short-term memory capacity of linear reservoir models to a high degree of precision. Using the framework, we study the effect of shortcut connections in the CRJ reservoir topology on its memory capacity.

scholarly journals Looking for more reliable biomarkers in breast cancer: Comparison between routine methods and RT-qPCR

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0255580
Author(s):  
Emanuele Caselli ◽  
Cristina Pelliccia ◽  
Valeria Teti ◽  
Guido Bellezza ◽  
Martina Mandarano ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dynamic Range ◽  
Mrna Level ◽  
Growth Factor Receptor ◽  
Complementary Method ◽  
Breast Cancer Biomarkers ◽  
Biomarker Testing ◽  
Epidermal Growth ◽  
Computational Pathology ◽  
High Degree

Purpose Decades of quality control efforts have raised the standards of immunohistochemistry (IHC), the principle method used for biomarker testing in breast cancer; however, computational pathology and reverse transcription quantitative PCR (RT-qPCR) may also hold promise for additional substantial improvements. Methods Herein, we investigated discrepancies in the assessment of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and marker of proliferation Ki67 comparing routinely obtained IHC (and FISH) data (ORI) with the results of manual (REV) and semi-automated (DIA) re-evaluation of the original IHC slides and then with RNA expression data from the same tissue block using the MammaTyper® (MT) gene expression assay. Results Correlation for ER and PR was high between ORI IHC and the other three study methods (REV, DIA and RT-qPCR). For HER2, 10 out of 96 discrepant cases can be detected between ORI and REV that involved at least one call in the equivocal category (except for one case). For Ki67, 22 (29.1%) cases were categorized differently by either REV alone (n = 17), DIA alone (n = 15) or both (n = 10) and 28 cases (29.2%) for RT-qPCR. Most of the discrepant Ki67 cases changed from low to high between the original and following assessment and belonged to the intermediate Ki67 expression range (between 9 and 30%). Conclusions Determination of the breast cancer biomarkers ER, PR, HER2 and Ki67 at the mRNA level shows high degree of correlation with IHC and compares well with correlations between original with subsequent independent manual or semi-automated IHC assessments. The use of methods with wider dynamic range and higher reproducibility such as RT-qPCR may offer more precise assessment of endocrine responsiveness, improve Ki67 standardization and help resolve HER2 cases that remain equivocal or ambiguous by IHC/FISH. In summary, our findings seem to configure RT-qPCR as a complementary method to be used in cases of either equivocal results or presenting, at the traditional determination assays, biomarkers expressions close to the cut-off values.

scholarly journals Structural changes of CAST soot during a thermal-optical measurement protocol

2019 ◽  
Author(s):  
Theresa Haller ◽  
Christian Rentenberger ◽  
Jannik C. Meyer ◽  
Laura Felgitsch ◽  
Hinrich Grothe ◽  
...  
Keyword(s):  
Structural Changes ◽  
Optical Measurement ◽  
Measurement Techniques ◽  
Domain Size ◽  
Carbonaceous Material ◽  
Total Carbon ◽  
Integrating Sphere ◽  
Heating Process ◽  
Continuous Change ◽  
Measurement Protocol

Abstract. Thermal-optical measurement techniques are widely used to classify carbonaceous material. The results of different methods for total carbon are comparable, but can vary by > 44 % for elemental carbon. One major cause of variation is the formation of pyrolyzed carbon during the heating process which occurs mainly in samples with a high amount of brown carbon (BrC). In this study the structural changes of two different CAST aerosol samples caused by the heating procedure in a thermal-optical instrument were investigated with UV-VIS and Raman spectroscopy, the Integrating Sphere technique and transmission electron microscopy. All analysis techniques showed significant structural changes for BrC rich samples at the highest temperature level (870 °C) in helium. The structure of the heated BrC-rich sample resembles the structure of an unheated BrC-poor sample. Heating the BrC rich sample to 870 °C increases the graphitic domain size within the material from 1.6 nm to 2 nm. Although the Raman spectra unambiguously show this increase of ordering only at the highest temperature step, UV-VIS and IS analyses show a continuous change of the optical properties also at lower temperatures. The sample with a negligible amount of BrC, however, did not show any significant structural changes during the whole heating procedure.

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