Predictions in ungauged basins (PUBs) are an increasingly important question in the water resource and quality management fields, especially for small watersheds where the phenomenon of data scarcity is prevalent. The transfer of hydrological parameters on the basis of regionalization is a common approach for solving PUB problems, and plenty of research has been undertaken on how to transfer calibrated parameters from gauged to ungauged watersheds. However, hydrological parameters estimation is substantially influenced by calibration objectives, which may affect model performance on the recipient watershed as well. In this paper the influence of calibration objectives on the transfer of parameter sets from one watershed to another is discussed. The HSPF hydrological model and the PEST automatic calibration model with four calibration objectives (squared error of daily flow, squared error of monthly flow, squared error of exceedance flow time, and sum of these squared errors) were applied. One gauged watershed of the Lake Dianchi Basin with daily flow data from 1999 to 2010 was calibrated by the combined HSPF-PEST model to obtain the transferrable parameters. Then the entire parameter sets were transferred to another neighborhood watershed, and model performance was tested by conventional goodness-of-fit statistics. Results show that (1) parameters transferred from all four calibration objectives perform well on the target watershed; (2) selection of calibration objective has a significant impact on model performance for both donor and recipient watersheds; and (3) the differences among objectives are similar in the two watersheds, suggesting that the objectives' features are transferrable. Therefore, the selection of calibration objective should be considered as a significant factor when transferring parameters to ungauged watersheds. (C) 2014 American Society of Civil Engineers.
Oxygenated volatile organic compounds (OVOCs) are important products of the photo-oxidation of hydrocarbons. They influence the oxidizing capacity and the ozone-forming potential of the atmosphere. In the summer of 2008, 2 months of emission restrictions were enforced in Beijing to improve air quality during the Olympic Games. Observational evidence reported in related studies that these control measures were efficient in reducing the concentrations of primary anthropogenic pollutants (CO, NOx and non-methane hydrocarbons, i.e., NMHCs) by 30-40%. In this study, the influence of the emission restrictions on ambient levels of OVOCs was explored using a neural network analysis with consideration of meteorological conditions. Statistically significant reductions in formaldehyde (HCHO), acetaldehyde (CH3CHO), methyl ethyl ketone (MEK) and methanol were found to be 12.9, 15.8, 17.1 and 19.6%, respectively, when the restrictions were in place. The effect of emission controls on acetone was not detected in neural network simulations, probably due to pollution transport from surrounding areas outside Beijing. Although the ambient levels of most NMHCs were reduced by similar to 35% during the full control period, the emission ratios of reactive alkenes and aromatics closely related to automobile sources did not present much difference (< 30%). A zero-dimensional box model based on the Master Chemical Mechanism version 3.2 (MCM3.2) was applied to evaluate how OVOC production responds to the reduced precursors during the emissions control period. On average, secondary HCHO was produced from the oxidation of anthropogenic alkenes (54%), isoprene (30%) and aromatics (15%). The importance of biogenic sources for the total HCHO formation was almost on par with that of anthropogenic alkenes during the daytime. Anthropogenic alkenes and alkanes dominated the photochemical production of other OVOCs such as acetaldehyde, acetone and MEK. The relative changes of modeled HCHO, CH3CHO, methyl vinyl ketone and methacrolein (MVK + MACR) before and during the pollution controlled period were comparable to the estimated reductions in the neural network, reflecting that current mechanisms can largely explain secondary production of those species under urban conditions. However, it is worth noting that the box model overestimated the measured concentrations of aldehydes by a factor of 1.4-1.7 without consideration of loss of aldehydes on aerosols, and simulated MEK was in good agreement with the measurements when primary sources were taken into consideration. These results suggest that the understanding of the OVOCs budget in the box model remains incomplete, and that there is still considerable uncertainty in particular missing sinks (unknown chemical and physical processes) for aldehydes and absence of direct emissions for ketones
A nonadditive hole-transporting material (HTM) of a triphenylamine derivative of N,N'-di(3-methylphenyl)-N,N'-diphenyl-4,4'-diaminobiphenyl (TPD) is used for the organic-inorganic hybrid perovskite solar cells. The power conversion efficiency (PCE) can be significantly enhanced by inserting a thin layer of 1,4,5,8,9,11-hexaazatriphenylenehexacarbonitrile (HAT-CN) without adding an ion additive because the hole-transporting properties improve. The short-circuit current density (J(sc)) increases from 8.5 to 13.1 mA/cm(2), the open-circuit voltage (V-oc) increases from 0.84 to 0.92 V, and the fill-factor (FF) increases from 0.45 to 0.59, which corresponds to the increase in PCE from 3.2% to 7.1%. Moreover, the PCE decreases by only 10% after approximately 1000 h without encapsulation, which suggests an alternative method to improve the stability of perovskite solar cells.
An indirect simulation-optimization model framework with enhanced computational efficiency and risk-based decision-making capability was developed to determine optimal total maximum daily load (TMDL) allocation under uncertainty. To convert the traditional direct simulation-optimization model into our indirect equivalent model framework, we proposed a two-step strategy: (1) application of interval regression equations derived by a Bayesian recursive regression tree (BRRT v2) algorithm, which approximates the original hydrodynamic and water-quality simulation models and accurately quantifies the inherent nonlinear relationship between nutrient load reductions and the credible interval of algal biomass with a given confidence interval; and (2) incorporation of the calibrated interval regression equations into an uncertain optimization framework, which is further converted to our indirect equivalent framework by the enhanced-interval linear programming (EILP) method and provides approximate-optimal solutions at various risk levels. The proposed strategy was applied to the Swift Creek Reservoir's nutrient TMDL allocation (Chesterfield County, VA) to identify the minimum nutrient load allocations required from eight sub-watersheds to ensure compliance with user-specified chlorophyll criteria. Our results indicated that the BRRT-EILP model could identify critical sub-watersheds faster than the traditional one and requires lower reduction of nutrient loadings compared to traditional stochastic simulation and trial-and-error (TAE) approaches. This suggests that our proposed framework performs better in optimal TMDL development compared to the traditional simulation-optimization models and provides extreme and non-extreme tradeoff analysis under uncertainty for risk-based decision making.
Satellite data and models suggest that oceanic productivity is reduced in response to less nutrient supply under warming. In contrast, anthropogenic aerosols provide nutrients and exert a fertilizing effect, but its contribution to evolution of oceanic productivity is unknown. We simulate the response of oceanic biogeochemistry to anthropogenic aerosols deposition under varying climate from 1850 to 2010. We find a positive response of observed chlorophyll to deposition of anthropogenic aerosols. Our results suggest that anthropogenic aerosols reduce the sensitivity of oceanic productivity to warming from -15.21.8 to -13.31.6PgCyr(-1)degrees C-1 in global stratified oceans during 1948-2007. The reducing percentage over the North Atlantic, North Pacific, and Indian Oceans reaches 40, 24, and 25%, respectively. We hypothesize that inevitable reduction of aerosol emissions in response to higher air quality standards in the future might accelerate the decline of oceanic productivity per unit warming.