Nitrous oxide emissions from 2008 to 2012 for agricultural lands in the conterminous United States

The soil N2O emissions data for the conterminous United States were generated by the DayCent ecosystem model using the crop and land-use histories for survey locations in the USDA-NRCS National Resources Inventory (NRI). The model also requires weather and soils data. Daily maximum/minimum temperature and precipitation data are based on gridded weather data from the PRISM Climate Data product. Soils data are obtained from Soil Survey Geographic Database (SSURGO). See Del Grosso et al. (2022) and US-EPA (2020) for more details about the simulations. Atmospheric inversions were conducted using the CarbonTracker Langrage framework (Nevison et al. 2018). These results provide total N2O fluxes for the domain using atmospheric observations and an inverse modeling, and are compared to the DayCent emissions to confirm seasonal patterns, particularly the role of freeze-thaw events in driving pulses of N2O emissions from agricultural lands.Nitrous oxide (N2O) is an important greenhouse gas (GHG) that also contributes to depletion of ozone in the stratosphere. Agricultural soils account for about 60% of anthropogenic N2O emissions. Most national GHG reporting to the UN Framework Convention on Climate Change assumes nitrogen (N) additions drive emissions during the growing season, but soil freezing and thawing during spring is also an important driver in cold climates. We show that both atmospheric inversions and newly implemented bottom-up modeling approaches exhibit large N2O pulses in the northcentral region of the United States during early spring and this increases annual N2O emissions from croplands and grasslands reported in the national GHG inventory by 11%. Considering this, emission accounting in cold climate regions is very likely under-estimated in most national reporting frameworks. Current commitments related to the Paris Agreement and COP 26 emphasize reductions of carbon compounds. Assuming these targets are met, the importance of accurately accounting and mitigating N2O increases once CO2 and CH4 are phased out. Hence, the N2O emission under-estimate introduces additional risks into meeting long term climate goals.US Forest Service 18-CR-11242305-109, US Department of Agriculture (USDA) UV-B Monitoring and Research Program, Colorado State University, under USDA National Institute of Food and Agriculture Grant 2016-34263-25763, and the USDA GHG and DayCent modeling NACA agreements (58-3012-9-012 and 58-3012-1-015

Reorganization of self-assembled DNA-based polymers using orthogonally addressable building blocks

Nature uses non-covalent interactions to achieve structural dynamic reconfiguration of biopolymers. Taking advantage of the programmability of DNA/DNA interactions we report here the rational design of orthogonal DNA-based addressable tiles that self-assemble into polymer-like structures that can be reconfigured by external inputs. The different tiles share the same sticky ends responsible for self-assembly but are rationally designed to contain a specific regulator-binding domain that can be orthogonally targeted by different DNA regulator strands. We show that by sequentially adding specific inputs it is possible to re-organize the formed structures to display well-defined distributions: homopolymers, random and block structures. The versatility of the systems presented in this study shows the ease with which DNA-based addressable monomers can be designed to create reconfigurable micron-scale DNA structures offering a new approach to the growing field of supramolecular polymers

Dynamical Casimir cooling in circuit QED systems

A transmission line coupled to an externally driven superconducting quantum interference device (SQUID) can exhibit the Dynamical Casimir Effect (DCE). Employing this setup, we quantize the SQUID degrees of freedom and show that it gives rise to a three-body interaction Hamiltonian with the cavity modes. By considering only two interacting modes from the cavities we show that the device can function as an autonomous cooler where the SQUID can be used as a work source to cool down the cavity modes. Moreover, this setup allows for coupling to all modes existing inside the cavities, and we show that by adding two other extra modes to the interaction with the SQUID the cooling effect can be enhanced.Comment: 13 pages, 6 figure

Why future nitrogen research needs the social sciences

Nitrogen management is on the cusp of becoming a major global policy issue — the international community is gradually acknowledging that the feasibility of an array of environmental, health and food security goals hinges on how humanity manages nitrogen as a resource and a pollutant over the coming decades. As a result, the nitrogen research agenda should expand to consider more policy-relevant questions, such as the power dynamics of the broader food system and the many influences on farmer decision-making. Doing so demands much closer collaboration between the natural and social sciences, from problem formulation to research execution, which requires overcoming a range of ideological, institutional and knowledge barriers

Quantification of the Chemical Chaperone 4-Phenylbutyric Acid (4-PBA) in Cell Culture Media via LC-HRMS: Applications in Fields of Neurodegeneration and Cancer

In recent years, 4-phenylbutyric acid (4-PBA), an FDA-approved drug, has increasingly been used as a nonspecific chemical chaperone in vitro and in vitro, but its pharmacodynamics is still not clear. In this context, we developed and validated a Liquid Chromatography–High Resolution Mass Spectrometry (LC-HRMS) method to quantify 4-PBA in NeuroBasal-A and Dulbecco’s Modified Eagle widely used cell culture media. Samples were injected on a Luna® 3 µm PFP(2) 100 Å (100 × 2.0 mm) column maintained at 40 °C. Water and methanol both with 0.1% formic acid served as mobile phases in a step gradient mode. The mass acquisition was performed by selected ion monitoring (SIM) in negative mode for a total run time of 10.5 min at a flow rate of 0.300 mL/min. The analogue 4-(4-Nitrophenyl)-Butyric Acid served as internal standard. Validation parameters were verified according to FDA and EMA guidelines. The quantification ranges from 0.38–24 µM. Inter and intraday RSDs (Relative Standard Deviations) were within 15%. The developed LC-HRMS method allowed the estimation of 4-PBA absorption and adsorption kinetics in vitro in two experimental systems: (i) 4-PBA improvement of protein synthesis in an Alzheimer’s disease astrocytic cell model; and (ii) 4-PBA reduction of endoplasmic reticulum stress in thapsigargin-treated melanoma cell lines. © 2023 by the authors

Approaches and concepts of modelling denitrification: increased process understanding using observational data can reduce uncertainties

Denitrification is a key but poorly quantified component of the Ncycle. Because it is difficult to measure the gaseous (NO$_{x}$, N$_{2}$O, N$_{2}$)and soluble (NO$_{3}$) components of denitrification with sufficientintensity, models of varying scope and complexity have beendeveloped and applied to estimate how vegetation cover, landmanagement and environmental factors such as soil type andweather interact to control these variables. In this paper we assessthe strengths and limitations of different modeling approaches,highlight major uncertainties, and suggest how differentobservational methods and process-based understanding can becombined to better quantify N cycling. Representation of howbiogeochemical (e.g. org. C., pH) and physical (e.g. soil structure)factors influence denitrification rates and product ratios combinedwith ensemble approaches may increase accuracy withoutrequiring additional site level model inputs

Chapter 18. DAYCENT Simulated Effects of Land Use and Climate on County Level N Loss Vectors in the USA

We describe the nitrogen (N) gas (NH3, NOx, N2O, N2) emission and NO3 leaching submodels used in the DAYCENT ecosystem model and demonstrate the ability of DAYCENT to simulate observed N2O emission and NO3 leaching rates for various sites representing different climate regimes, soil types, and land uses. DAYCENT simulated seven major crops, grazing lands, and potential native vegetation at the county level for the United States. At the national scale, NO3 leaching was the major loss vector, accounting for 86%, 66%, and 56% of total N losses for cropped soils, grazed lands, and native vegetation, respectively. NH3 volatilization + NOx emissions made up the majority of national N gas losses, accounting for 58%, 89%, and 86% of N gas losses from cropped soils, grazed lands, and native vegetation, respectively. However, there was considerable spatial variability in the N loss vectors, with leaching accounting for less than 20% of total N losses and NOx + NH3 emissions accounting for less than 50% of N gas losses in some counties. Land use area weighted mean annual N losses were 43.9 (SD = 26.8) and 12.3 (SD = 22.2)kg N/ha for cropped/grazed and native systems, respectively. Area weighted mean annual N gas losses were 11.8 (SD = 4.8) and 5.4 (SD = 2.1)kg N/ha for cropped/grazed and native systems, respectively. Total N losses and NO3 leaching tended to increase as N inputs and precipitation increased, and as soils became coarser textured. Total N gas losses also increased with N inputs and as soils became coarser textured, but N2O and N2 made up a larger portion of N gas losses as soils became finer textured and as precipitation increased

Assessing precipitation, evapotranspiration, and NDVI as controls of U.S. Great Plains plant production

Productivity throughout the North American Great Plains grasslands is generally considered to be water limited, with the strength of this limitation increasing as precipitation decreases. We hypothesize that cumulative actual evapotranspiration water loss (AET) from April to July is the precipitation-related variable most correlated to aboveground net primary production (ANPP) in the U.S. Great Plains (GP). We tested this by evaluating the relationship of ANPP to AET, precipitation, and plant transpiration (Tr). We used multi-year ANPP data from five sites ranging from semiarid grasslands in Colorado and Wyoming to mesic grasslands in Nebraska and Kansas, mean annual NRCS ANPP, and satellite-derived normalized difference vegetation index (NDVI) data. Results from the five sites showed that cumulative April-to-July AET, precipitation, and Tr were well correlated (R2: 0.54–0.70) to annual changes in ANPP for all but the wettest site. AET and Tr were better correlated to annual changes in ANPP compared to precipitation for the drier sites, and precipitation in August and September had little impact on productivity in drier sites. April-to-July cumulative precipitation was best correlated (R2 = 0.63) with interannual variability in ANPP in the most mesic site, while AET and Tr were poorly correlated with ANPP at this site. Cumulative growing season (May-to-September) NDVI (iNDVI) was strongly correlated with annual ANPP at the five sites (R2 = 0.90). Using iNDVI as a surrogate for ANPP, we found that county-level cumulative April–July AET was more strongly correlated to ANPP than precipitation for more than 80% of the GP counties, with precipitation tending to perform better in the eastern more mesic portion of the GP. Including the ratio of AET to potential evapotranspiration (PET) improved the correlation of AET to both iNDVI and mean county-level NRCS ANPP. Accounting for how different precipitation-related variables control ANPP (AET in drier portion, precipitation in wetter portion) provides opportunity to develop spatially explicit forecasting of ANPP across the GP for enhancing decision-making by land managers and use of grassland ANPP for biofuels

One year after on Tyrrhenian coasts: The ban of cotton buds does not reduce their dominance in beach litter composition

In January 2019, Italy banned the sale of plastic cotton buds, which is one of the most abundant litter items entering the sea and then washing ashore. However, since the ban came into force, no studies have been carried out to assess whether the measure has actually led to the reduction of plastic cotton buds accumulating on Italian coasts. Here we aim at evaluating the effectiveness of the ban in reducing the amount of cotton buds reaching sandy beaches of the Tyrrhenian coast. Specifically, we monitored the accumulation of beach litter for one year since the ban came into force. By surveying eight coastal sites from winter 2019 to winter 2020, we collected a total of 52,824 items mostly constituted by plastic debris (97.6%). We found that cotton buds were the most abundant item (42.3% of total litter), followed by plastic (28.5%) and polystyrene (5.43%) fragments. Our preliminary assessment suggests that the ban has so far not led to a sensible reduction in the amount of cotton buds entering the marine ecosystem. This was to be expected since implementation strategies are still lacking (i.e. no economic sanctions can be imposed in case of non-compliance) and bans are differently implemented among countries facing the Mediterranean Sea, calling for law enforcement and implementation at the national and international levels