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The environmental consequences of residue removal practices to support cellulosic biofuel production remain poorly understood. In the U.S. Midwest, corn (Zea mays L.) stover removal combined with no-till practices may increase or decrease soil N2O emissions by influencing soil moisture, temperature, and nutrient dynamics, yet empirical evidence from long-term field experiments is inconsistent. We investigated the effects of residue management (residue retained or removed) and tillage (chisel-till or no-till) on cumulative soil nitrous oxide (N2O) emissions, grain yield, and yield-scaled N2O emissions in a 3-year study initiated 10 years after treatment implementation in a long-term, continuous corn experiment in Illinois, United States. Crop yields were affected by treatment in only one of three study years, with the combination of residue removal and no-till reducing yields compared to both chisel-till treatments. Cumulative N2O emissions, soil inorganic N concentrations, and yield-scaled N2O emissions differed over the 3-year period and were significantly affected by tillage, with no response to residue management. In 2 years, no-till decreased cumulative N2O emissions and yield-scaled N2O emissions by an average of 64% and 60%, respectively. Correlations between daily N2O fluxes and soil moisture, temperature, and inorganic N concentrations suggested that the relative importance of these variables changed depending on year and treatment. While more research across a range of sites and management practices is needed, our findings support previous studies which have challenged IPCC methodology assumptions regarding the effects of residue removal on N2O emissions. We conclude there is inherent difficulty in predicting the impacts of residue removal due to the complexity of soil processes underlying N2O emissions coupled with inter-annual weather variability in this rainfed continuous corn system. Future efforts to evaluate the net greenhouse gas emissions of cellulosic biofuel production may benefit from accounting for this uncertainty.

Meeting crop nitrogen (N) demand while minimizing N losses to the environment has proven difficult despite significant field research and modeling efforts. To improve N management, several real-time N management tools have been developed with a primary focus on enhancing crop production. However, no coordinated effort exists to simultaneously address sustainability concerns related to N losses at field- and regional-scales. In this perspective, we highlight the opportunity for incorporating environmental effects into N management decision support tools for United States maize production systems by integrating publicly available crop models with grower-entered management information and gridded soil and climate data in a geospatial framework specifically designed to quantify environmental and crop production tradeoffs. To facilitate advances in this area, we assess the capability of existing crop models to provide in-season N recommendations while estimating N leaching and nitrous oxide emissions, discuss several considerations for initial framework development, and highlight important challenges related to improving the accuracy of crop model predictions. Such a framework would benefit the development of regional sustainable intensification strategies by enabling the identification of N loss hotspots which could be used to implement spatially explicit mitigation efforts in relation to current environmental quality goals and real-time weather conditions. Nevertheless, we argue that this long-term vision can only be realized by leveraging a variety of existing research efforts to overcome challenges related to improving model structure, accessing field data to enhance model performance, and addressing the numerous social difficulties in delivery and adoption of such tool by stakeholders.

The fragility, fouling and dull wettability of membrane materials greatly limit their widespread applications. Herein, inspired by the natural activation of nitrogen in soil by lightning, an electrically driven flow-through catalysis separation membrane reactor (CSMR) with switchable wettability is developed. Catalytically active centers and responsive switches can be firmly assembled on the membrane reactor with the support of MOFs to provide catalytic and wettability modulation functions. Remarkably, the wettability of the membrane reactor can transition from superhydrophobic to superhydrophilic states in a mere 10 s under applied voltage. It achieves the efficient separation of various oil–water mixtures (oil–water separation efficiency above 99%) and electrocatalytic oxidation degradation (over 95% catalytic efficiency and flux above 4500 L m−2 h−1). The design of this multifunctional intelligent membrane reaction provides a scheme for the green and efficient treatment of actual wastewater, which may have broad potential in the construction and design of smart materials and electronic devices. [ABSTRACT FROM AUTHOR]

Anionic defects of H− (H∙O) and oxygen vacancies with trapped electrons (V∙O) have been built in the lattice of a hydrothermally derived perovskite (Ba5Nb4O15, BNO) by CaH2 reduction in Ar flow at 600 °C for 12 h. The formed anionic defects in the CaH2-reduced BNO (CaBNO) have been found to improve drastically the ammonia synthesis activity of Ru/CaBNO by donating electrons from both H∙O and/or V∙O to Ru atoms. The stoichiometry of H∙O and V∙O has been determined by TPR and TPO method, respectively. The H∙O defects have been proved to react with N2 under ammonia synthesis conditions via TPD, XPS measurements and isotope (D2) reaction, which provides secondary pathways for ammonia synthesis. Kinetic studies revealed that oxygen vacancies accept spilledover H atoms from Ru particles to alleviate the H2 poisoning effect. Cs-promoter has been demonstrated to accelerate the formation of anionic defects in CaBNO under ammonia synthesis reactions. Anionic defects (V∙O and H∙O) formed in the lattice of Ba5Nb4O15 perovskite via CaH2-reduction drastically promote the ammonia synthesis activity of Cs-Ru/CaBNO catalyst [ABSTRACT FROM AUTHOR]

The aim of this study was to prepare a novel pH-sensitive smart film based on the addition of purple garlic peel extract (PGE) and TiO2 nanoparticles in a sodium alginate (SA)/polyvinyl alcohol (PVA) matrix to monitor the freshness of beef. FT-IR spectroscopy revealed the formation of stronger interaction forces between PVA/SA, PGE, and TiO2 nanoparticles, which showed good compatibility. In addition, the addition of PGE improved the tensile strength and elongation at break of the composite film, especially in different pH environments, and the color response was obvious. The addition of 1% TiO2 nanoparticles significantly improved the mechanical properties of the film, as well as the light barrier properties of the film. PGE could effectively be uniformly dispersed into the composite film, but it also had a certain slow-release effect on the release of PGE. PGE had high sensitivity under different pH conditions with rich color changes, and the color showed a clear color change from red to yellow-green when the pH increased from 1 to 14. The same change was observed when it was added to the film. In particular, by applying this film to the process of beef preservation, we judged the freshness of beef by monitoring the changes in the TVB-N value and pH value during the storage process of beef and found that the film showed obvious color changes during the storage process of beef, from blue (indicating freshness) to red (indicating non-freshness), and finally to yellow-green (indicating deterioration), which indicated that the color change of the film and the freshness of the beef maintained a highly consistent. [ABSTRACT FROM AUTHOR]