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At least 145 records · Page 8

A Comparative Analysis of Micrometeorological Determinants of Evapotranspiration Rates Within a Heterogeneous Urban Environment

Variability in micrometeorological conditions and their influence on estimated reference evapotranspiration (RET) rates were evaluated across a heterogeneous urban environment. Micrometeorological data sets (incoming solar radiation, air temperature, relative humidity and wind speed) were collected over a one-year period at six weather stations in New York City, NY (USA). Weather stations are located at four new urban green space monitoring sites and two airports. Reference evapotranspiration (RET) rates were estimated from the micrometeorological data sets for a short reference surface at a daily time-step using the ASCE Standardized Reference Evapotranspiration Equation, a Penman-Monteith based combination equation. Nonparametric comparative statistical analyses (Kruskal-Wallis) revealed statistically significant differences (at significance level α = 0.05) in micrometeorological conditions and estimated RET rates between the six sites. On a cumulative annual basis, estimated RET varied by up to 40 percent between the sites. A new technique for adjusting weather data collected at one location (e.g. regional airports) for use at another location (e.g. interior engineered urban green spaces) was evaluated. The study highlights the importance, for accurate estimation of ET, of onsite micrometeorological data sets, but concludes that additional research is needed to more thoroughly characterize micrometeorological variability across heterogeneous urban environments, and also to evaluate the influence of non-meteorological determinants, e.g. vegetation type, soil/media type, media moisture conditions and anthropogenic heat fluxes, on urban ET.

Urban environment↗

Heterogeneity of Bulk Oxygen Isotopic Compositions in Anhydrous Interplanetary Dust Particles

Introduction: Anhydrous interplanetary dust particles are one of the least altered ancient solar systemmaterials. Their bulk chemical compositions match those of CI chondrites within a factor of 2-3, except for carbonwhich is enriched in both anhydrous and hydrated IDPs by ~4x CI [1]. Hydrous IDPs often show 16O-poor isotopiccompositions, likely due to the interaction with isotopically heavy H2O [2]. Anhydrous IDPs are interpreted tooriginate from comets from the outer solar system [3]. Oxygen isotopic data for these materials is scarce, but resultspoint to a wider range of compositions [4]. This heterogeneity might be a result of mixing between a 16O-rich and a16O-poor reservoir formed via self-shielding and photodissociation of CO [5]. Here, we report bulk oxygen isotopiccompositions of three anhydrous IDPs in context of their mineralogical composition and discuss possible origins ofisotopic heterogeneity. Experimental: Bulk chemical composition and mineralogy of 70 nm thin ultramicrotomed sections of threeanhydrous IDPs (L2099A7, L2099A8, and L2071AB1) were analyzed using a Thermo Scientific Titan Themis G360-300 TEM equipped with a four-quadrant energy-dispersive X-ray detector (Super-X G2) at University ofMünster. Bulk oxygen isotopic compositions were measured using a NanoSIMS 50 at the Max-Planck-Institut fürChemie in Mainz. A focused Cs+ ion beam (~1 pA, ~100 nm) was rastered over a field of view varying from 5 x 5 to6 x 6 μm2, depending on particle size for 15 layers. Negative secondary ions of 16O, 17O, 18O, 12C14N, and 28Si werecollected on electron multipliers. The 16OH contribution to the 17O peak was 1-2 ‰. As a standard, a matrix regionof meteorite CR2 Queen Alexandra Range (QUE) 99177 was used, whose oxygen isotopic composition wasmeasured by [6]. Results and Discussion: Particles A7 and A8 are both fine-grained, consisting mostly of small, 100 nm-sizedequilibrated aggregates (EA). Both particles exhibit discontinuous magnetite rims with thicknesses up to 50 nm inA7 and 100 nm in A8 on the outsides. In Particle AB1, the upper part of the particle consists of a few EAs, while thelower part contains lots of small GEMS grains with 100-200 nm diameter clustered together. Magnetite rims arenearly absent, the rare rims reaching maximum 20 nm thickness, indicating that AB1 is of more primitive naturethan the other two IDPs [1]. Furthermore, it contains several diffuse GEMS-like areas, identified by an amorphoussilicate groundmass with small nano-inclusions of Fe,Ni-metal and Fe-sulfides. All three particles are subsolar forall major element/Si ratios. Mean S/Si of particles A7 and A8 is 0.046 and 0.048, respectively, while it is an order ofmagnitude higher in AB1 (0.184). This reflects the higher degree of thermal alteration in A7 and A8, resulting in theloss of volatile S and oxidation of Fe-sulfides and FeNi-metal to magnetite as present in particle rims. A8 is rather16O-poor with δ17OSMOW = 7.8 ± 3.4 ‰ and δ18OSMOW = 9.5 ± 3.1 ‰ (1σ), followed by A7 with δ17OSMOW = − 0.8 ±4.6 ‰ and δ18OSMOW = −2.2 ± 3.4 ‰. In contrast to that, AB1 has the most 16O-rich bulk composition with δ17OSMOW= −24.2 ± 5.4 ‰ and δ18OSMOW = −25.3 ± 3.6 ‰. All investigated IDPs plot slightly above the CCAM line aspreviously reported for other anhydrous IDPs [4], maybe due to a contribution from circumstellar dust from AGBstars enriched in 17O [7]. The 16O-rich composition of AB1 is similar to the most 16O-rich anhydrous IDP U2015D21measured by [8] which is dominated by GEMS [9] and the GEMS-rich IDP GM4-2 reported by [10]. Nevertheless,it is unlikely that GEMS are the carrier for the 16O-rich composition of AB1 because most GEMS have O isotopiccompositions indistinguishable from terrestrial values, although errors on these analyses are large [11]. The isotopicheterogeneity is best explained by contribution of grains from different regions in the protoplanetary disk, samplingdifferent O isotope reservoirs, created by self-shielding and photodissociation of CO. This process resulted in 16O-rich CO gas and 16O-poor H2O that froze as ice-mantles onto dust grains [12]. Alternatively, the higher degree ofheating in A7 and A8 could have influenced isotopic fractionation, because higher δ17,18O values are reported fromthe regions of the atmosphere where small particles are heated and oxidized, as observed for the thermal alteration ofcosmic spherules [13]. Acknowledgements: We would like to thank NASA Astromaterials Acquisition & Curation Office for providing IDPsamples and DFG for funding this project (VO1816/5-1)

B Schulz↗

Investigating Amino Acid Heterogeneity in Milligram-Scale Samples of the Murchison CM2 Carbonaceous Chondrite

Analyses of different aliquots of the Tagish Lake meteorite have resulted in amino acid abundance variations of an order of magnitude or more, even when performed using the same techniques, by the same personnel, in the same laboratories (e.g., Simkus et al. 2019). Up to ~five-fold variations have been observed for specific amino acids in different samples of the same meteorite, such as α aminoisobutryic acid (AIB) in Murchison. These variations are often attributed differing sample composition or differing alteration history, neither of which is mutually exclusive. Distinguishing between these two explanations is challenging and time consuming, requiring detailed mineralogical analyses to be performed in conjunction with high precision organics analysis. The potential for innate sample-level heterogeneity presents a significant complication when parsing the effects of different processes or conditions during preparation of meteorite samples for analysis, as differences in organic yields or abundances could be due to differences in laboratory processing or differences among the samples themselves. In this work, we investigated the degree of innate organic heterogeneity present in a single ~250 mg chip of divided into 21 samples.

A. S. Burton↗

Heterogeneous Outgassing Regions Identified on Active Centaur 29P/Schwassmann–Wachmann 1

Centaurs are transitional objects between primitive trans-Neptunian objects and Jupiter-family comets. Their compositions and activities provide fundamental clues regarding the processes affecting the evolution of and interplay between these small bodies. Here we report observations of centaur 29P/Schwassmann–Wachmann 1 (29P) with the James Webb Space Telescope (JWST). We identified localized jets with heterogeneous compositions driving the outgassing activity. We employed the NIRSpec mapping spectrometer to study the fluorescence emissions of CO and obtain a definitive detection of CO 2 for this target. The exquisite sensitivity of the instrument also enabled carbon and oxygen isotopic signatures to be probed. Molecular maps reveal complex outgassing distributions, such as jets and anisotropic morphology, which indicate that 29P’s nucleus is dominated by active regions with heterogeneous compositions. These distributions could reflect that it has a bilobate structure with compositionally distinct components or that strong differential erosion takes place on the nucleus. As there are no missions currently planning to visit a centaur, these observations demonstrate JWST’s unique capabilities in characterizing these objects.

Sara Faggi↗

Applicability of the Effective-Medium Approximation to Heterogeneous Aerosol Particles.

The effective-medium approximation (EMA) is based on the assumption that a heterogeneous particle can have a homogeneous counterpart possessing similar scattering and absorption properties. We analyze the numerical accuracy of the EMA by comparing superposition T-matrix computations for spherical aerosol particles filled with numerous randomly distributed small inclusions and Lorenz-Mie computations based on the Maxwell-Garnett mixing rule. We verify numerically that the EMA can indeed be realized for inclusion size parameters smaller than a threshold value. The threshold size parameter depends on the refractive-index contrast between the host and inclusion materials and quite often does not exceed several tenths, especially in calculations of the scattering matrix and the absorption cross section. As the inclusion size parameter approaches the threshold value, the scattering-matrix errors of the EMA start to grow with increasing the host size parameter and or the number of inclusions. We confirm, in particular, the existence of the effective-medium regime in the important case of dust aerosols with hematite or air-bubble inclusions, but then the large refractive-index contrast necessitates inclusion size parameters of the order of a few tenths. Irrespective of the highly restricted conditions of applicability of the EMA, our results provide further evidence that the effective-medium regime must be a direct corollary of the macroscopic Maxwell equations under specific assumptions.

aerosols↗

Heterogeneous Chemistry Important in the Polar Stratosphere

Aircraft emissions have been thought to enhance the formation of polar stratospheric clouds in the Arctic winter, and therefore heterogeneous reactions on the surfaces of these clouds may accelerate the polar ozone depletion.

polar stratosphere heterogeneous chemistry ozone d↗

Heterogeneous Reactions of HNO3(g) + NaCl(s) Yields HCL(g) + NaNO3(s) and N2O5(g) + NaCl(s) Yields ClNo2(g) + NaNO3(s)

The heterogeneous reactions of HNO3(g) + NaCl(s) Yields HCL(g) + NaNO3(s) and N2O5(g) + NaCl(s) Yields ClNo2(g) + NaNO3(s)were investigated over a temperature range of 223-296 K in a flow-tube reactor coupled to a quadrupole mass spectrometer. The implications for volcanic enhancement of the HCl and HNO3 column density in the lower stratosphere are discussed.

heterogeneous↗

A Knowledge Graph Framework for Organizing Heterogeneous Datasets for Utilization in Classical and Quantum Computing: Current Challenges and Future Directions

"The escalating impact of climate change induced extreme weather events in urban, suburban, and rural environments demands a rethink of how we have been using the single event-based or use-case-based knowledge graph models. The lack of representation in interaction within environmental variables found in literature led to the development of a novel framework that reflects the true nature of the interconnectedness in our environment. We propose an Environmental Interaction Knowledge Graph (EIKG) framework. This general EIKG framework works as the basis for interconnected environmental events by knitting interrelated events such as hurricanes leading to storm surges, which lead to flood events that could cause mudslides, landslides, etc., The cascading nature of one event leading to another related event in the environment requires an adequate understanding of each event using contextual information before conducting any data-driven analytics. This vision paper showcases how the EIKG:floods, EIKG:wildfire EIKG:landslides, etc, can be derived from a base case framework of EIKG as those individual events are interconnected with some common denominator variables. As an example, the precipitation variable is used in the flood case study as well as in the wildfire case study, as excessive precipitation levels lead to floods, and lack of precipitation leads to droughts and wildfires. We identify the precipitation variable as a “common-denominator-variable” in extreme weather events that play a key role in modeling the environment leading to different extreme weather events based on the variability of that variable (varying values where low precipitation leads to drought, and high values lead to floods). We use the insights gained from EIKG to conduct classical and Quantum Machine Learning (QML) based data analysis on the research questions developed. Our preliminary study shows how the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC) are used along with the classical machine learning models to compare the model accuracies. Our study elaborates on how a quantitative analysis uses state-of-the-art machine learning techniques that include implementing both classical and quantum machine learning models and developing the knowledge graph. The EIKG is used to organize heterogeneous datasets and integrate the relations to case-specific extreme weather events such as floods. The study uses datasets such as county-to-country residential mobility data, socioeconomic datasets from the US Census Bureau, climate and weather-related Earth Observational data from NASA, and critical infrastructure data from the Homeland Infrastructure datasets."

Knowledge Graphs, Quantum Computing, Heterogenous ↗