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Presentation for AMPP conference specifically for technical community of interest (TCI) meeting associated with conference
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This paper investigates the potential of coupling Thermal Energy Storage (TES) with Advanced Reactors (ARs) to address uncertainties posed by climate change in deep decarbonized power systems. The TES Use-case Team at Idaho National Laboratory (INL) has examined the potential of storing thermal energy from ARs during low demand periods and optimizing discharge during peak-priced hours, in both steady-state and transient conditions. Building on this groundwork, this study bridges the gaps in optimal sizing of the sub-system of TES-coupled AR systems using Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON), INL?s framework for grid optimization. By applying this framework, we present statistically-robust optimal charge, discharge including balance of plant (BOP), and storage sizing for the High-Temperature Gas-Cooled Reactor (HTGR) with 203 MWth output. To this end, we generated synthetic price samples for 30 years using 2018 ? 2021 real-time market data from ERCOT, PJM and MISO. Our results reveals that the TES-coupled HTGR system is highly effective in maximizing revenue from electricity sales. We observed a substantial increase of 40 % in ERCOT and a noteworthy 15 % increase in PJM and MISO when compared to the conventional BOP without TES. This improvement is achieved through regionally-tailored sub-system sizing, which ranges from 398 to 416 MWth for the discharge system and 610 to 1029 MWth for the TES. We find that the average electricity price directly impacts the overall economics, while price volatility influences storage size. Additional sensitivity analyses were performed to access the impact of key assumptions on system economics and sizing, differentiating the optimization window (i.e., 24 ? 219 hours of chronological observations) and by imposing storage continuity condition in tracking TES cycles. We observed that at the 120-hour of the optimization window, a reasonable balance between computation time and accuracy was achieved. Our analysis also highlights the significance of conducting multi-day cycle analysis (> 120-hour) for TES to capture interaction between electricity prices and storage dynamics, providing a comprehensive understanding of TES behavior that AR developers should integrate into their plant designs.
Integrated soil-crop management (ISCM) has been shown as an effective strategy to increase efficiency and yield while its soil microbial community structure and function remain unclear. We evaluated changes in soil physicochemical factors, bacterial community structure responses, and the contributions of soil properties and bacterial communities to summer maize-winter wheat yield and GHG emissions through an ISCM experiment [T1 (local smallholder farmers practice system), T2 (improved management system), T3 (high–yield production system), and T4 (optimized management system)], which could provide scientific guidance for sustainable development of soil in summer maize-winter wheat rotation system. The results showed that the optimized ISCM could improve the soil quality, which significantly changed the soil bacterial community structure to reduce GHG emissions and increase yield. The co-occurrence network density of T3 was increased significantly. The Acidobacteria (class) and OM190 (class) were enriched in T2 and T4. The Frankiales (order) and Gaiellales (order) were enriched in T3. However, the changes in different crop growth stages were different. At the wheat jointing stage and maize mature stage, T4 could enhance carbon-related functional groups, such as aromatic hydrocarbon degradation and hydrocarbon degradation, to increase the soil organic carbon content. And at the maize tasseling stage, T4 could enhance nitrogen-related functional groups. And soil bacteria structure and function indirectly affected annual yield and GHG emission. T2 and T4 exhibited a similar soil microbial community. However, the yield and nitrogen use efficiency of T2 were reduced compared to those of T4. The yield of T3 was the highest, but the GHG emission increased and soil pH and nitrogen use efficiency decreased significantly. Therefore, T4 was a suitable management system to improve soil quality and soil bacterial community structure and function to decrease GHG emissions and increase the yield of the summer maize-winter wheat rotation system.
Coastal waters such as those found in the Baltic Sea already suffer from anthropogenic related problems including increased algal blooming and hypoxia while ongoing and future climate change will likely worsen these effects. Microbial communities in sediments play a crucial role in the marine energy- and nutrient cycling, and how they are affected by climate change and shape the environment in the future is of great interest. The aims of this study were to investigate potential effects of prolonged warming on microbial community composition and nutrient cycling including sulfate reduction in surface (∼0.5 cm) to deeper sediments (∼ 24 cm). To investigate this, 16S rRNA gene amplicon sequencing was performed, and sulfate concentrations were measured and compared between sediments in a heated bay (which has been used as a cooling water outlet from a nearby nuclear power plant for approximately 50 years) and a nearby but unaffected control bay. The results showed variation in overall microbial diversity according to sediment depth and higher sulfate flux in the heated bay compared to the control bay. A difference in vertical community structure reflected increased relative abundances of sulfur oxidizing- and sulfate reducing bacteria along with a higher proportion of archaea, such as Bathyarchaeota, in the heated compared to the control bay. This was particularly evident closer to the sediment surface, indicating a compression of geochemical zones in the heated bay. These results corroborate findings in previous studies and additionally point to an amplified effect of prolonged warming deeper in the sediment, which could result in elevated concentrations of toxic compounds and greenhouse gases closer to the sediment surface.
Objectives COVID-19 survivors suffer from persistent mental distress and impaired quality of life (QOL) after recovery from the infection. However, the symptom-symptom interaction between these psychological variables remained unexplored. The present study aimed to determine the symptom network of mental distress (depression, anxiety, sleep disturbance, fatigue, and post-traumatic stress disorder) and their association with QOL among 535 COVID-19 survivors 1 year after hospital discharge. Methods 9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder Scale, Chalder fatigue scale, Impact of Event Scale-Revised, Pittsburgh Sleep Quality Index, and 36-Item Short-Form Health Survey were applied to measure depression, anxiety, fatigue, PTSD, sleep disturbances, and QOL, respectively. Two networks were estimated using Gaussian graphical model. Network 1 consisted of mental symptoms to determine the central and bridge symptoms. Network 2 additionally included QOL to determine which mental symptoms were mostly related to QOL. Results 60% of the COVID-19 survivors experienced mental distress 1 year after hospital discharge. Uncontrollable and excessive worry, psychomotor symptoms, intrusion, and daytime dysfunction were the most central symptoms. Daytime dysfunction and fatigue (especially mental fatigue and loss of energy) served as the bridge symptoms across the mental distress network and exhibited the most substantial association with QOL. Conclusion Our study demonstrated several key symptoms that played a vital role in mental distress and QOL among COVID-19 survivors. Prompt screening and targeted interventions for these symptoms might hold great promise in preventing mental distress and improving QOL in COVID-19 survivors.
The variations in the characteristics of the tropopause are sensitive indicators for the climate system and climate change. By using Atmospheric Radiation Measurement (ARM) radiosonde data that were recorded at the extratropical Southern Great Plains (SGP) and Arctic North Slope of Alaska (NSA) sites over an 18-year period (January 2003 to December 2020), this study performs a fine-scale comparison of the climatological tropopause features between these two sites that are characterized by different climates. The static stability increases rapidly above the tropopause at both sites, indicating the widespread existence of a tropopause inversion layer. The structures of both the tropopause inversion layer and the stability transition layer are more obvious at NSA than at SGP, and the seasonal variation trends of the tropopause inversion layer and stability transition layer are distinctly different between the two sites. A fitting method was used to derive the fitted tropopause height and tropopause sharpness (λ). Although this fitting method may determine a secondary tropopause rather than the primary tropopause when multiple tropopause heights are identified on one radiosonde profile, the fitted tropopause heights generally agree well with the observed tropopause heights. Broad tropopause sharpness values (λ > 2 km) occur more frequently at SGP than at NSA, resulting in a greater average tropopause sharpness at SGP (1.0 km) than at NSA (0.6 km). Significant positive trends are exhibited by the tropopause heights over the two sites, with rates of increase of 23.7 ± 6.5 m yr ⁻1 at SGP and 28.0 ± 4.0 m yr ⁻1 at NSA during the study period.
Compared to low doses of gamma irradiation (γ-IR), high-charge-and-energy (HZE) particle IR may have different biological response thresholds in cardiac tissue at lower doses, and these effects may be IR type and dose dependent. Three- to four-month-old female CB6F1/Hsd mice were exposed once to one of four different doses of the following types of radiation: γ-IR 137Cs (40-160 cGy, 0.662 MeV), 14Si-IR (4-32 cGy, 260 MeV/n), or 22Ti-IR (3-26 cGy, 1 GeV/n). At 16 months post-exposure, animals were sacrificed and hearts were harvested and archived as part of the NASA Space Radiation Tissue Sharing Forum. These heart tissue samples were used in our study for RNA isolation and microarray hybridization. Functional annotation of twofold up/down differentially expressed genes (DEGs) and bioinformatics analyses revealed the following: (i) there were no clear lower IR thresholds for HZE- or γ-IR; (ii) there were 12 common DEGs across all 3 IR types; (iii) these 12 overlapping genes predicted various degrees of cardiovascular, pulmonary, and metabolic diseases, cancer, and aging; and (iv) these 12 genes revealed an exclusive non-linear DEG pattern in 14Si- and 22Ti-IR-exposed hearts, whereas two-thirds of γ-IR-exposed hearts revealed a linear pattern of DEGs. Thus, our study may provide experimental evidence of excess relative risk (ERR) quantification of low/very low doses of full-body space-type IR-associated degenerative disease development.
School-based mindfulness programs (SBMPs) have gained global popularity. Yet, there is a need for more rigorous procedures to develop and assess them. This study aimed to address these limitations by examining the effectiveness of a Portuguese SBMP, called SER + FELIZ(mente). The final sample included 190 third and fourth-graders: 99 in the SBMP group and 91 in a wait-list group. Effects on attentional control, emotional regulation and wellbeing were examined in the short term (T2) and 6 months later (T3). We also tested the moderating role of age, gender, and baseline scores. Using a multilevel modeling approach, results showed a clear benefit of SBMP on emotional wellbeing at T2 but not T3. Despite SBMP students surpassing wait-list students in attentional control, cognitive reappraisal, and social wellbeing at T2, these effects were due to a levelling off among SBMP students, coupled with a decline among wait-list students from T1 to T2. These effects were moderated by age at T3. While universal improvements were limited, our SBMP seemed to have acted as a shield against school stressors (i.e., likely, test anxiety at T2). This opens a new avenue for research concerning the role of SBMPs in preventing (rather than repairing) mental-health issues in elementary students.
Bioenergy with carbon capture and storage (BECCS) can sequester atmospheric CO2, while producing electricity. The CO2 avoidance cost (CAC) is used to calculate the marginal cost of avoided CO2 emissions for BECCS as compared to other established energy technologies. A comparative analysis using four different reference-case power plants for CAC calculations is performed here to evaluate the CO2 avoidance cost of BECCS implementation. Results from this work demonstrate that BECCS can generate electricity at costs competitive with other neutral emissions technologies, while simultaneously removing CO2 from the atmosphere. Approximately 73% of current coal power plants are approaching retirement by the year 2035 in the U.S. After considering CO2 sequestered from the atmosphere and coal power plant CO2 emissions displaced by BECCS, CO2 emissions can be reduced by 1.4 billion tonnes per year in the U.S. alone at a cost of $88 to $116 per tonne of CO2 removed from the atmosphere, for 10% to 90% of available biomass used, respectively. CAC calculations in this paper indicate that BECCS can help the U.S. and other countries transition to a decarbonized electricity grid, as simulations presented in this paper predict that BECCS power plants operate at lower CACs than coal plants with CCS.
California has experienced a surge in wildfires, prompting research into contributing factors, including weather and climate conditions. This study investigates the complex, multiscale interactions between large-scale climate patterns, such as the Boreal Summer Intraseasonal Oscillation (BSISO), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO) and their influence on moisture and temperature fluctuations, and wildfire dynamics in California. The combined impacts of PDO and BSISO on intraseasonal fire weather changes; the interplay between fire weather index (FWI), relative humidity, vapor pressure deficit (VPD), and temperature in assessing wildfire risks; and geographical variations in the relationship between the FWI and climatic factors within California are examined. The study employs a multi-pronged approach, analyzing wildfire frequency and burned areas alongside climate patterns and atmospheric conditions. The findings reveal significant variability in wildfire activity across different climate conditions, with heightened risks during specific BSISO phases, La-Niña, and cool PDO. The influence of BSISO varies depending on its interaction with PDO. Temperature, relative humidity, and VPD show strong predictive significance for wildfire risks, with significant relationships between FWI and temperature in elevated regions (correlation, r > 0.7, p ≤ 0.05) and FWI and relative humidity along the Sierra Nevada Mountains (r ≤ -0.7, p ≤ 0.05).
We used the research quartz crystal microbalance (RQCM) to monitor regulatory effects of plasmin and trypsin in the presence of their inhibitor α2-antiplasmin. The gold surface of quartz crystals was modified with a β-casein layer that served as a substrate for protease digestion. The addition of plasmin or trypsin as well as their mixtures with α2-antiplasmin resulted in an increase of resonant frequency, f, and in a decrease of motional resistance, Rm, depending on the molar ratio of protease: antiplasmin. At equimolar concentrations of protease and α2-antiplasmin (5 nM:5 nM) full inhibition of protease activity took place. Monitoring of plasmin activity on an hourly and daily basis revealed a prominent effect of autolysis and decrease of plasmin activity in freshly activated samples. The degree of inhibition as well as plasmin half-life (t1/2 = 2.48 ± 0.28 days) connected with its degradation was determined.
High levels of sulfur dioxide (SO 2 ) due to human activities pose a serious air pollution issue in China, especially in urban agglomerations. However, limited research has investigated the impact of anthropogenic emissions on higher SO 2 concentrations in urban regions compared to rural areas in China. Here, we analyzed the trends in SO 2 concentrations from 1980 to 2021 in China using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) dataset. SO 2 column concentrations from the Copernicus Atmosphere Monitoring Service (CAMS) and the Ozone Monitoring Instrument (OMI) during the years 2007–2021 were also examined for validation and comparison purposes. Eight representative areas, including four urban regions (Pearl River Delta [PRD], Beijing-Tianjin-Hebei [BTH], Yangtze River Delta [YRD], and Sichuan Basin [SCB]) and four rural regions (Northeast Region [NER], Mongolian Region [MR], West Region [WR], and Tibetan Plateau Region [TR]) were selected for the analysis. Overall, a significant but fluctuating increase in SO 2 concentrations over China was observed during 1980–2021. During 1980–1997 and 2000–2010, there was an increase in SO 2 concentration, while during 1997–2000 and 2010–2021, a decreasing trend was observed. The average increase in SO 2 concentration was approximately 16 times higher in urban regions than in the rural background. We also found that SO 2 dynamics were highly associated with expansion of urban areas, population density, and gross domestic product. Nonetheless, since 2007, SO 2 concentrations have exhibited a downward trend, which is mainly attributed to the air pollution policies implemented by the Chinese government. Our findings highlight the need for further studies on the impact of SO 2 on regional climate change in China.
These files contain data from soil and root samples use in this publication. The R script uses this data to perform the statistical analysis used in the publication.
Atmospheric ice-nucleating particles (INPs) play an important role in determining the phase of clouds, which affects their albedo and lifetime. A lack of data on the spatial and temporal variation of INPs around the globe limits our predictive capacity and understanding of clouds containing ice. Automated instrumentation that can robustly measure INP concentrations across the full range of tropospheric temperatures is needed in order to address this knowledge gap. In this study, we demonstrate the functionality and capacity of the new Portable Ice Nucleation Experiment (PINE) to study ice nucleation processes and to measure INP concentrations under conditions pertinent for mixed-phase clouds, with temperatures from about -10 to about -40°C. PINE is a cloud expansion chamber which avoids frost formation on the cold walls and thereby omits frost fragmentation and related background ice signals during the operation. The development, working principle and treatment of data for the PINE instrument is discussed in detail. We present laboratory-based tests where PINE measurements were compared with those from the established AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber. Within experimental uncertainties, PINE agreed with AIDA for homogeneous freezing of pure water droplets and the immersion freezing activity of mineral aerosols. Results from a first field campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory in Oklahoma, USA, from 1 October to 14 November 2019 with the latest PINE design (a commercially available PINE chamber) are also shown, demonstrating PINE's ability to make automated field measurements of INP concentrations at a time resolution of about 8 min with continuous temperature scans for INP measurements between -10 and -30°C. During this field campaign, PINE was continuously operated for 45 d in a fully automated and semi-autonomous way, demonstrating the capability of this new instrument to also be used for longer-term field measurements and INP monitoring activities in observatories.