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298 records · Page 17

Performance of low-cost monitors to assess household air pollution

Highlights: • We assessed PM{sub 2.5} and CO low-cost monitors in semi-controlled and field studies. • Devices experienced high failure rate and susceptibility to environmental changes. • Low-cost monitors tested may not be ready to replace more established methods. Exposure to household air pollution is a leading cause of morbidity and mortality globally. However, due to the lack of validated low-cost monitors with long-lasting batteries in indoor environments, most epidemiologic studies use self-reported data or short-term household air pollution assessments as proxies of long-term exposure. We evaluated the performance of three low-cost monitors measuring fine particulate matter (PM{sub 2.5}) and carbon monoxide (CO) in a wood-combustion experiment conducted in one household of Spain for 5 days (including the co-location of 2 units of HAPEX and 3 units of TZOA-R for PM{sub 2.5} and 3 units of EL-USB-CO for CO; a total of 40 unit-days). We used Spearman correlation (ρ) and Concordance Correlation Coefficient (CCC) to assess accuracy of low-cost monitors versus equivalent research-grade devices. We also conducted a field study in India for 1 week (including HAPEX in 3 households and EL-USB-CO in 4 households; a total of 49 unit-days). Correlation and agreement at 5-min were moderate-high for one unit of HAPEX (ρ = 0.73 / CCC = 0.59), for one unit of TZOA-R (ρ = 0.89 / CCC = 0.62) and for three units of EL-USB-CO (ρ = 0.82–0.89 / CCC = 0.66–0.91) in Spain, although the failure or malfunction rate among low-cost units was high in both settings (60% of unit-days in Spain and 43% in India). Low-cost monitors tested here are not yet ready to replace more established exposure assessment methods in long-term household air pollution epidemiologic studies. More field validation is needed to assess evolving sensors and monitors with application to health studies.

54 ENVIRONMENTAL SCIENCES↗

Optimization-Driven Scenario Grouping

Scenario decomposition algorithms for stochastic programs compute bounds by dualizing all nonanticipativity constraints and solving individual scenario problems independently. Here, we develop an approach that improves on these bounds by reinforcing a carefully chosen subset of nonanticipativity constraints, effectively placing scenarios into groups. Specifically, we formulate an optimization problem for grouping scenarios that aims to improve the bound by optimizing a proxy metric based on information obtained from evaluating a subset of candidate feasible solutions. We show that the proposed grouping problem is NP-hard in general, identify a polynomially solvable case, and present two formulations for solving the problem: a matching formulation for a special case and a mixed-integer programming formulation for the general case. We use the proposed grouping scheme as a preprocessing step for a particular scenario decomposition algorithm and demonstrate its effectiveness in solving standard test instances of two-stage 0–1 stochastic programs. Using this approach, we are able to prove optimality for all previously unsolved instances of a standard test set. Additionally, we implement this scheme as a preprocessing step for PySP, a publicly available and widely used implementation of progressive hedging, and compare this grouping approach with standard grouping approaches on large-scale stochastic unit commitment instances. Finally, the idea is extended to propose a finitely convergent algorithm for two-stage stochastic programs with a finite feasible region.

97 MATHEMATICS AND COMPUTING↗

Humic Substances Extracted by Alkali Are Invalid Proxies for the Dynamics and Functions of Organic Matter in Terrestrial and Aquatic Ecosystems

The conceptual rigor of using organic materials extracted from soil by alkali, called humic substances, as proxies for soil organic matter has been questioned for almost 180 years. However, the humic substances paradigm, i.e., the understanding that alkali-extracted humic substances are newly synthesized materials with unique properties that are distinct from non-humic organic matter, continues to be propagated throughout the literature. Here, we revisit the mechanistic background of the extraction process to show that alkaline extraction is unable to discriminate for the chemical history of a compound. For this reason, alkaline extraction cannot distinguish between (i) materials that have undergone secondary synthesis or humification (“humic” substances), and (ii) materials that are decorated with ionizable functional groups for other reasons, such as oxidative depolymerization (“non-humic” substances). While this mechanistic consideration alone renders invalid a distinction between humic substances and non-humic substances based on alkaline extraction, we further show that the evidence available to date does not support the assumption that processes of secondary synthesis create quantitatively significant proportions of “chemically reactive, yet recalcitrant” materials in natural environments. Any definition of humic substances that invokes both alkaline extraction and secondary synthesis is thus flawed on at least two accounts: (i) alkaline extraction is unable to achieve its purpose of separating humic from non-humic substances, and (ii) the assertion that the extracted materials have unique molecular properties as a consequence of secondary synthesis cannot be proven because alkaline extraction cannot separate materials created by secondary synthesis from other, ionizable organic compounds. Finally, we point out that since the definition of humic substances is tied to the alkaline-extraction procedure, neither the existence of operationally defined humic substances in the environment nor their chemical integrity during the course of alkaline extraction can be independently verified. We conclude that organic materials extracted by alkali require appropriate nomenclature and rigorous definition to merit consideration in teaching, research, and application.

54 ENVIRONMENTAL SCIENCES↗

Improving estimates of sub-daily gross primary production from solar-induced chlorophyll fluorescence by accounting for light distribution within canopy

Solar-induced chlorophyll fluorescence (SIF) has long been regarded as a proxy for photosynthesis and has shown superiority in estimating gross primary production (GPP) compared to traditional vegetation indices, especially in evergreen ecosystems. However, current SIF-based GPP estimations regard the canopy as a large leaf and seldom consider the impact of interactions among light, canopy structure, and leaf physiology. In this study, we proposed GPP estimation models with different descriptions of light–structure–physiology interactions (including the layered model, the two-leaf model, and the layered two-leaf model) and compared their performances with the big-leaf model using half-hourly (or hourly) observations at evergreen needleleaf forest sites. First, we found that the big-leaf model underestimated GPP, especially at noon. All models showed higher accuracy than that of the big-leaf model. Second, we investigated the diurnal dynamics of GPP estimations in each canopy layer and found that models with a two-leaf assumption captured the diurnal variations in GPP better than that with the layered assumption. Here we also deduced that the poor performance of the big-leaf model was related to its overestimation of the overall light stress on the redox state of PSII reaction centers (qL). Finally, we noticed that the qL at the canopy scale had lower sensitivity to light change than the single-leaf qL and that the light response of canopy-scale qL was influenced by the leaf area index during seasonal cycles. Overall, this study describes methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale. Further, it indicates the need to consider the description of light distribution within the canopy in next-generation terrestrial biosphere models, even if they incorporate SIF to constrain their parameterization. Thus, upscaling the established leaf-scale mechanistic SIF-GPP relationship or findings to canopy-scale applications still requires much work, especially when there are significant changes in environmental conditions and their within-canopy distributions.

59 BASIC BIOLOGICAL SCIENCES↗

A reduced order model to analytically infer atmospheric CO 2 concentration from stomatal and climate data

To address questions related to the acceleration or deceleration of the global hydrological cycle or links between the carbon and water cycles over land, reliable data for past climatic conditions based on proxies are required. In particular, the reconstruction of palaeoatmospheric CO 2 content (C a ) is needed to assist the separation of natural from anthropogenic C a variability and to explore phase relations between C a and air temperature T a time series. Both T a and C a are needed to fingerprint anthropogenic signatures in vapor pressure deficit, a major driver used to explain acceleration or deceleration phases in the global hydrological cycle. Current approaches to C a reconstruction rely on a robust inverse correlation between measured stomatal density in leaves (ν) of many plant taxa and C a . There are two methods that exploit this correlation: The first uses calibration curves obtained from extant species assumed to represent the fossil taxa, thereby restricting the suitable taxa to those existing today. The second is a hybrid eco-hydrological/physiological approach that determines C a with the aid of systems of equations based on quasi-instantaneous leaf-gas exchange theories and fossil stomatal data collected along with other measured leaf anatomical traits and parameters. In this contribution, a reduced order model (ROM) is proposed that derives C a from a single equation incorporating the aforementioned stomatal data, basic climate (e.g. temperature), estimated biochemical parameters of assimilation and isotope data. The usage of the ROM is then illustrated by applying it to isotopic and anatomical measurements from three extant species. The ROM derivation is based on a balance between the biochemical demand and atmospheric supply of CO 2 that leads to an explicit expression linking stomatal conductance to internal CO 2 concentration (C i ) and C a . The resulting expression of stomatal conductance from the carbon economy of the leaf is then equated to another expression derived from water vapor gas diffusion that includes anatomical traits. When combined with isotopic measurements for long-term C i /C a , C a can be analytically determined and is interpreted as the time-averaged C a that existed over the life-span of the leaf. Key advantages of the proposed ROM are: 1) the usage of isotopic data provides constraints on the reconstructed atmospheric CO 2 concentration from ν, 2) the analytical form of this approach permits direct links between parameter uncertainties and reconstructed C a , and 3) the time-scale mismatch between the application of instantaneous leaf-gas exchange expressions constrained with longer-term isotopic data is reconciled through averaging rules and sensitivity analysis. The latter point was rarely considered in prior reconstruction studies that combined models of leaf-gas exchange and isotopic data to reconstruct C a from ν. The proposed ROM is not without its limitations given the need to a priori assume a parameter related to the control on photosynthetic rate. Our work here further explores immanent constraints for the aforementioned photosynthetic parameter.

54 ENVIRONMENTAL SCIENCES↗

Interactive Effects of Climate Change and Decomposer Communities on the Stabilization of Wood-Derived Carbon Pools: Catalyst for a New Study

Globally, forest soils store ~two-thirds as much carbon (C) as the atmosphere. Although wood makes up the majority of forest biomass, the importance of wood contributions to soil C pools is unknown. Even with recent advances in the mechanistic understanding of soil processes, integrative studies tracing C input pathways and biological fluxes within and from soils are lacking. Therefore, our research objectives were to assess the impact of different fungal decay pathways (i.e., white-rot versus brown-rot)—in interaction with wood quality, soil temperature, wood location (i.e., soil surface and buried in mineral soil), and soil texture—on the transformation of woody material into soil CO 2 efflux, dissolved organic carbon (DOC), and soil C pools. The use of 13 C-depleted woody biomass harvested from the Rhinelander, WI free-air carbon dioxide enrichment (Aspen-FACE) experiment affords the unique opportunity to distinguish the wood-derived C from other soil C fluxes and pools. We established 168 treatment plots across six field sites (three sand and three loam textured soil). Treatment plots consisted of full-factorial design with the following treatments: 1. Wood chips from elevated CO 2 , elevated CO 2 + O 3 , or ambient atmosphere AspenFACE treatments; 2. Inoculated with white rot (Bjerkandera adusta) or brown rot (Gloeophyllum sepiarium) pure fungal cultures, or the original suite of endemic microbial community on the logs; and 3. Buried (15cm in soil as a proxy for coarse roots) or surface applied wood chips. We also created a warming treatment using open-topped, passive warming chambers on a subset of the above treatments. Control plots with no added wood (“no chip control”) were incorporated into the research design. Soils were sampled for initial δ 13 C values, CN concentrations, and bulk density. A subset of plots were instrumented with lysimeters for sampling soil water and temperature data loggers for measuring soil temperatures. To determine the early pathways of decomposition, we measured soil surface CO 2 efflux, dissolved organic C (DOC), and DO 13 C approximately monthly over two growing seasons from a subsample of the research plots. To determine the portion of soil surface CO 2 efflux attributable to wood-derived C, we used Keeling plot techniques to estimate the associated δ 13 C values of the soil CO 2 efflux. We measured the δ 13 CO 2 once during the peak of each growing season. Initial values for soil δ 13 C values and CN concentrations averaged across the six sites were -26.8‰ (standard error = 0.04), 2.46% (se = 0.11), and 0.15% (se = 0.01), respectively. The labeled wood chips from the Aspen FACE treatments had an average δ13C value of -39.5‰ (se 0.10). The >12 ‰ isotopic difference between the soil and wood chip δ 13 C values provides the basis for tracking the wood-derived C through the early stages of decomposition and subsequent storage in the soil. Across our six research sites, average soil surface CO 2 efflux ranged from 1.04 to 2.00 g CO 2 m -2 h -1 for the first two growing seasons. No wood chip controls had an average soil surface CO 2 efflux of 0.67 g CO 2 m -2 h -1 or about half of that of the wood chip treatment plots. Wood-derived CO 2 efflux was higher for loam textured soils relative to sands (0.70 and 0.54 g CO 2 m -2 h -1 , respectively; p = 0.045)), for surface relative to buried wood chip treatments (0.92 and 0.39 g CO 2 m -2 h -1 , respectively; p < 0.001), for warmed relative to ambient temperature treatments (0.99 and 0.78 g CO 2 m -2 h -1 , respectively; 0.004), and for natural rot relative to brown and white rots (0.93, 0.82, and 0.78 g CO 2 m -2 h -1 , respectively; p = 0.068). Our first two growing seasons of soil surface CO 2 efflux data show that wood chip location (i.e., surface vs. buried chip application) is very important, with surface chips loosing twice the wood-derived CO 2 . The DOC data support this trend for greater loss of ecosystem C from surface chips. This has strong implications for the importance of root and buried wood for ecosystem C retention. This strong chip location effect on wood-derived C loss was significantly modified by soil texture, soil temperature, decomposer communities, and wood quality as effected by potential future CO 2 and O 3 levels.

54 ENVIRONMENTAL SCIENCES↗

Rapid Development of Hybrid Perovskites and Novel Tandem Architectures

Multijunction solar cells based on epitaxially grown III-V materials hold the record for solar energy power conversion efficiency (PCE). However, due to the high cost of fabricating these devices, they are typically only used for concentrator cells and space applications. The overarching goal of this project was to develop low-cost printable hybrid perovskite (HP) materials appropriate and optimized for tandem solar cells with high power conversion efficiency under “1 Sun” illumination. Key results and findings over the course of the project we: Developed higher-performance high-bandgap (1.75 eV) perovskite materials and devices. In particular, we explored tens-of-thousands of compositions for high bandgap perovskites, achieving quasi-Fermi level splitting of 1.35 eV for a 1.75 eV bandgap material. We achieved World-record open circuit voltages from single junction p-i-n devices, 1.24 V from 1.75 eV bandgap material, which is what is preferable for tandems with a PCE of 14.3% using a guanidinium/formanadinium/ cesium alloyed lead iodobromide. We also developed a series of World-record efficiency devices at higher band-gaps based on 2D/3D perovskites using PEA. Developed higher-performance low-bandgap (1.35 eV) perovskite materials and devices. In particular, we developed a 1.35 eV bandgap perovskite of composition MAPb0.5Sn0.5(I0.8Br0.2)3 and showed its superiority to MAPb0.75Sn0.25I3. High efficiency solar cells were fabricated using PEDOT:PSS and doped-ICBA as HTL and ETL, respectively. Short circuit currents of 25.7 mA/cm2 and PCEs of 17.1% were obtained. Developed mechanically stacked 4-terminal CIGS-Perovskite tandems with PCE of 18.8% and monolithic 2-terminal CIGS-Perovskite tandems with PCE of 8.5%. The low efficiency of the monolithic device is a result of the high surface roughness of the solution processed CIGS bottom cells. This is not an intrinsic problem for CIGS-perovskite tandems, but does mean that smooth evaporated or sputtered CIGS films likely need to be used, unless a polishing step is employed. Developed monolithic 2-terminal Perovskite-Perovskite tandems with a stabilized PCE of 18.5%. This was the World-record perovskite-perovskite monolithic tandems for over a year in 2017-2018. Revealed that light is not an essential component of the so-called “light-induced” phase segregation. By using charge injection in the dark and electroluminescence, we showed that the presence of electrons in the conduction band and hole in the valence band is sufficient to drive the nearly ubiquitously observed phase segregation in high bandgap perovskites. Developed a new method to simultaneously measure absolute intensity photoluminescence and photoconductivity and use them to obtain simultaneous in-situ measurement of quasi-Fermi level splitting and diffusion length. This is important since it provides a proxy for device Voc and device Jsc. In addition, 67 papers were published with support from this award that detail many more advances in the field, including numerous publications in high impact journals such as Nature Photonics, Advanced Materials, ACS Energy Letters, and Energy and Environmental Science.

14 SOLAR ENERGY↗

Improving galaxy cluster selection with the outskirt stellar mass of galaxies

The number density and redshift evolution of optically selected galaxy clusters offer an independent measurement of the amplitude of matter fluctuations, 𝑆 8 . However, recent results have shown that clusters chosen by the redMaPPer algorithm show richness-dependent biases that affect the weak lensing signals and number densities of clusters, increasing uncertainty in the cluster mass calibration and reducing their constraining power. Here, in this work, we evaluate an alternative cluster proxy, outskirt stellar mass, 𝑀 out , defined as the total stellar mass within a [50, 100] kpc envelope centered on a massive galaxy. This proxy exhibits scatter comparable to redMaPPer richness, 𝜆, but is less likely to be subject to projection effects. We compare the Dark Energy Survey Year 3 redMaPPer cluster catalog with a 𝑀 out selected cluster sample from the Hyper-Suprime Camera survey. We use weak lensing measurements to quantify and compare the scatter of 𝑀 out and 𝜆 with halo mass. Our results show 𝑀 out has a scatter consistent with 𝜆, with a similar halo mass dependence, and that both proxies contain unique information about the underlying halo mass. We find 𝜆-selected samples introduce features into the measured Δ⁢Σ signal that are not well fit by a log-normal scatter only model, absent in 𝑀 out selected samples. Our findings suggest that 𝑀 out offers an alternative for cluster selection with more easily calibrated selection biases, at least at the generally lower richnesses probed here. Combining both proxies may yield a mass proxy with a lower scatter and more tractable selection biases, enabling the use of lower mass clusters in cosmology. Finally, we find the scatter and slope in the 𝜆 −𝑀 out scaling relation to be 0.49 ±0.02 and 0.38 ±0.09.

79 ASTRONOMY AND ASTROPHYSICS↗

Calibrating the absolute magnitude of type Ia supernovae in nearby galaxies using [O II ] and implications for H 0

The present state of cosmology is facing a crisis where there is a fundamental disagreement in measurements of the Hubble constant ($H_{0}$), with significant tension between the early and late Universe methods. Type Ia supernovae (SNe Ia) are important to measuring $H_{0}$ through the astronomical distance ladder. However, there remains potential to better standardize SN Ia light curves by using known dependencies on host galaxy properties after the standard light curve width and colour corrections have been applied to the peak SN Ia luminosities. To explore this, we use the 5-yr photometrically identified SNe Ia sample obtained by the Dark Energy Survey, along with host galaxy spectra obtained by the Australian Dark Energy Survey. Using host galaxy spectroscopy, we find a significant trend with the equivalent width (EW) of the [O II ] $\lambda \lambda$ 3727, 29 doublet, a proxy for specific star formation rate, and Hubble residuals. We find that the correlation with [O II ] EW is a powerful alternative to the commonly used mass step after initial light-curve corrections. Applying this [O II ] EW correction to 20 SNe Ia in calibrator galaxies observed with WiFeS, we examined the impact on SN Ia absolute magnitudes and $H_{0}$. Our [O II ] EW corrections result in $H_{0}$ values ranging between 73.04 and 73.51 $km$ $s^{-1} \, Mpc^{-1}$, with a combined statistical and systematic uncertainty of $\sim 1.31$ $km$ $s^{-1} \, Mpc^{-1}$. However, even with this additional correction, the impact of host galaxy properties in standardizing SNe Ia appears limited in reducing the current tension ($\sim 5\sigma$) with the cosmic microwave background result for $H_{0}$.

79 ASTRONOMY AND ASTROPHYSICS↗