Nitrogen oxides (NOx) are major atmospheric pollutants contributing to acid rain and photochemical smog. Selective catalytic reduction with ammonia (NH3-SCR) is a widely adopted technology for NOx removal, where catalyst design critically governs low-temperature efficiency. Graphene-based catalysts demonstrate exceptional potential in this context due to their tunable surface chemistry, high electron mobility, and thermal stability. This review comprehensively analyzes synthesis strategies, including chemical vapor deposition (CVD), sol–gel, hydrothermal, and solvothermal methods, and their correlation with catalytic morphology and activity. We specifically elucidate how oxygen/nitrogen functional groups and defect engineering enhancing NOx adsorption activation while mitigating sulfur poisoning through spatial confinement effects. The integration of computational modeling with experimental characterization reveals structure–activity relationships in graphene-supported metal clusters. Current challenges in scalable manufacturing and long-term stability under humid conditions are critically assessed, providing guidelines for advancing graphene catalysts toward industrial implementation.
This study addresses the energy crisis resulting from the excessive consumption of fossil fuels and the pollution associated with biomass and plastic waste. It presents an innovative microwave-assisted co-gasification technology for rice husks and waste plastics. The aim is to resolve critical issues such as the low syngas production rate, low heating value, and the propensity for clogging when plastics are gasified independently in conventional biomass gasification. Rice husks and low-density polyethylene (LDPE) are transformed into composite particles using low-temperature melt blending granulation technology, resulting in stable, continuous, and controllable feeding. This process demonstrates a dual synergistic mechanism in which steam acts as both a microwave absorber and an in-situ hydrogen supply agent. Additionally, the co-gasification of rice husks and LDPE enhances gas yield and heating value. Furthermore, dolomite significantly improves gas composition by adsorbing CO2. This study achieved a gas yield of 550.36 mL/g, a lower heating value of syngas (LHVg) of 28.76 MJ/Nm3, a carbon conversion efficiency (CCE) of 38.79%, and a cold gasification efficiency (CGE) of 54.02% under the conditions of collaborative optimization (850 degrees C, LDPE addition ratio 50%, steam flow rate 20 mL/h, and Dolomite/Mixed raw materials mass ratio 6/10). These findings offer an innovative process pathway that integrates anti-clogging mechanisms with high energy efficiency for the valuable conversion of waste biomass and plastics. Furthermore, this advancement plays a crucial role in engineering support for promoting the green energy economy and achieving carbon neutrality goals.
Organizations pursuing activities that advance the public interest often require support from their local communities, but such support may be harder to come by in more racially diverse communities. In this study, we argue that this negative effect of racial diversity on support for organizations serving the public interest will be weaker the more inclusive the community, especially where community inclusion is accompanied by shared values among members of different groups and where the organizations themselves are racially representative. We test and find support for these predictions by looking at one specific type of public service organization: public schools in the United States. Specifically, we find that community support for public schools-both generally in terms of local spending per pupil and specifically as the bond amounts residents vote to approve-is negatively associated with racial diversity within a school district, but this negative relation only holds for less inclusive communities where members of different groups are less likely to live close to each other or to have social ties with each other. We further find that this moderating effect of community inclusion is complemented by shared values and organizational representativeness, so that diversity has the most negative effect in less inclusive communities where members of different races differ in their political beliefs and schools are relatively segregated, and no significant effect in inclusive communities with shared values and integrated schools. Our study sheds new light on the conditions under which organizations seeking to address grand challenges can benefit from strong community support.
Characterizing the mechanisms and galaxy properties conducive to the escape of ionizing (LyC) emission is necessary to accurately model the Epoch of Reionization and identify the sources that powered it. Using Hubble Space Telescope data, the Ly α and Continuum Origins Survey (LaCOS) is the first program to obtain uniform, multiwavelength subkiloparsec imaging for a large sample (42) of galaxies observed in LyC and enable statistically robust studies between LyC and resolved galaxy properties. Here, we characterize the morphology and galaxy merger properties of LaCOS galaxies and investigate their connection with the escape fraction of LyC emission f esc LyC . We find strong anticorrelations between f esc LyC and size ( r 20 , r 50 , and r 80 ) measured in filters containing emission from star-forming regions, and with the asymmetry and clumpiness in F150LP, a filter tracing UV continuum and Ly α . We find that ≥48% of LaCOS galaxies, and ≥41% of LaCOS LyC-emitters are visually classified as galaxy mergers. Galaxies robustly identified as mergers in LaCOS are at advanced stages of interaction, close to coalescence. The f esc LyC properties of robust mergers and low-probability mergers cannot be differentiated statistically, and we only find significant difference between the two populations in terms of their sizes and LyC luminosity: robust mergers having larger values. We conclude that (i) f esc LyC tends to be larger in galaxies with a small number of compact, centrally located, UV-emitting star-forming regions, (ii) mergers at advanced stages of interaction represent a sizable fraction of LyC-emitting samples at z ∼ 0.3, and (iii) mergers can facilitate the escape of LyC photons from galaxies.
In a warming climate, spatiotemporal changes in precipitation and temperature can impact hydrologic processes and thus the quality of freshwater ecosystems. This study evaluates the performance of 35 downscaled and bias corrected Coupled Model Intercomparison Project phase 6 (CMIP6) general circulation models (GCMs) from NASA's Earth Exchange Global Daily Downscaled Projections (NEX-GDDP, 0.258 resolution) by comparing their historical simulations (1950-2014) of precipitation and near-surface air temperature with those from the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) reanalysis across the contiguous United States. Two complementary metrics are employed: the Wasserstein distance (WD) to assess distributional similarity and the structural similarity index measure (SSIM) to quantify spatial consistency on a monthly scale. The results reveal systematic uncertainties: The NEX-GDDP-CMIP6 simulations struggle to reproduce the warm-season spatial organization and temporal trends of precipitation in regions predominantly influenced by mesoscale convective systems. Additionally, they exhibit the lowest SSIM scores for cold-season temperatures, highlighting challenges in simulating snow-albedo feedback mechanisms, cloud-radiative processes, and boundary layer dynamics. The models are ranked based on the similarity of their historical simulations for both precipitation and temperature. In summary, IPSL-CM6A-LR leads in monthly distributional proximity, while MIROC-ES2L leads in monthly spatial similarity for total precipitation and mean temperature. Regionally, MIROC-ES2L performs best in the Midwest, Northern Great Plains, Northwest, and Southern Plains, whereas NorESM2-LM, FGOALS-g3, and GFDL-CM4-gr2 lead in the Northeast, Southeast, and Southwest, respectively. The spatial similarity analysis of maps of temporal trends reveals that BCC-CSM2-MR is the top model across contiguous United States (CONUS).
