Accumulating evidence indicates that N2O emission factors (EFs) vary with nitrogen additions and environmental variations. Yet the impact of the latter was often ignored by previous EF determinations. We developed piecewise statistical models (PMs) to explain how the N2O EFs in agricultural soils depend upon various predictors such as climate, soil attributes, and agricultural management. The PMs are derived from a new Bayesian Recursive Regression Tree algorithm. The PMs were applied to the case of EFs from agricultural soils in China, a country where large EF spatial gradients prevail. The results indicate substantial improvements of the PMs compared with other EF determinations. First, PMs are able to reproduce a larger fraction of the variability of observed EFs for upland grain crops (84%, n=381) and paddy rice (91%, n=161) as well as the ratio of EFs to nitrogen application rates (73%, n=96). The superior predictive accuracy of PMs is further confirmed by evaluating their predictions against independent EF measurements (n=285) from outside China. Results show that the PMs calibrated using Chinese data can explain 75% of the variance. Hence, the PMs could be reliable for upscaling of N2O EFs and fluxes for regions that have a phase space of predictors similar to China. Results from the validated models also suggest that climatic factors regulate the heterogeneity of EFs in China, explaining 69% and 85% of their variations for upland grain crops and paddy rice, respectively. The corresponding N2O EFs in 2008 are 0.840.18% (as N2O-N emissions divided by the total N input) for upland grain crops and 0.650.14% for paddy rice, the latter being twice as large as the Intergovernmental Panel on Climate Change Tier 1 defaults. Based upon these new estimates of EFs, we infer that only 22% of current arable land could achieve a potential reduction of N2O emission of 50%.
Over the last 20 years, much attention has been paid to renewable energy technology. Photovoltaic is a promising alternative to conventional fossil fuels. Dye-sensitized solar cells (DSCs) attract notable interest, not only due to their high efficiency and environmentally friendly nature, but also their easy fabrication and relatively low manufacture costs. Despite the high efficiencies, iodine/triiodine electrolytes have some disadvantages, such as the corrosion of the metallic electrodes and the sealing materials. It also absorbs visible light around 430 nm. Therefore, it is important to exploit the iodine-free redox couple in DSCs. An organic disulfide material of 2,5-dimercapto-1,3,4-thiadiazole (DMcT) is proved here to reduce and oxidize independently via homopolymerization and depolymerization. DMcT has been applied as cathode active material for lithium rechargeable batteries. Meanwhile, the self-redox property could be used as redox mediator in lieu of iodine/triiodine electrolytes. DMcT can be oxidized by self-polymerizing into PDMcT, which can be reduced by depolymerizing back to DMcT. In contrast to the conventional redox couples consisted of two different materials, DMcT can independently act as the redox mediator, which is the main difference between DMcT and the redox couples reported previously. Dye-sensitized solar cells consist of mesoporous TiO2, N719 dye, and this novel electrolyte achieved power conversion efficiency of 1.6% under 100 mW.cm(-2) simulated sunlight (AM 1.5G) and a higher efficiency of 2.6% at weak illumination (13 mW.cm(-2)), implying its promising application prospect. Although the conversion efficiency is relatively low to the iodine/triiodine-based DSCs, this novel single self-redox mediator provides a new promising way to the iodine-free dye-sensitized solar cells.
This paper extends the current literatures on the relation between fund expenses and fund flows using data from Taiwan. Our findings for the Taiwan market differ from previous studies on the U.S. market. Specifically, we find no support for the notion of “out of sight, out of mind”. For Taiwan mutual funds, net flows and inflows are negatively related to operating expenses but not front-end loads. The discrepancy between our results and those reported for the U.S. market may be attributed to the fee structure in Taiwan, where operating expenses are much higher than front-end loads and seem to have a bigger impact on fund performance. The negative relation between net flows (inflows) and operating expenses is more pronounced for funds with high institutional investor participation and funds charging high operating expenses. However, investor types show no significant impact on the relations between front-end loads and various measures of fund flows.