Estimating the Impact of Land Use Change on the Soil Erosion Hazard in the Zambezi River Basin

The formulation of the environmentally sound and sustainable policy for land use and water resources management requires development of methods necessary to predict the consequences of various human activities on the environment. The IIASA Water Resources Project (WAT) addresses this issue in several ways, one of them is the development of a Decision Support System for Large River Basins. Its objective is to elaborate a set of models and PC-AT interactive software package capable of analyzing problems that may arise in developing hydropower and irrigation systems, land use management and agricultural activity. The Zambezi river basin was selected as a case study for the implementation of the above methodology. This paper is devoted to soil erosion problem in the Zambezi river basin. Its importance for water resources planners arises inter alia from the fact that erosion processes may seriously influence the operation of reservoir systems due to silt deposition diminishing storage capacity. The model for estimating soil erosion hazard was used in combination with a number of land use scenarios. For these scenarios areas subject to particularly high erosion hazard were selected for the Zambezi. The paper presents a good starting point for further investigations on land use/climate/water resources interface

Mag het een onsje meer zijn? : een studie naar de Duitse varkensvleeskolom

De Duitse varkensvleesindustrie is van groot en toenemend belang voor de Nederlandse varkenshouderijkolom. Om de primaire varkenshouders goed te kunnen adviseren heeft Rabobank opdracht gegeven om een analyse te laten uitvoeren van deze markt. Op basis van deze analyse zijn aanbevelingen opgesteld voor Nederlandse zeugenhouders en vleesvarkenhouders om de huidige goede positie te handhaven of te verbetere

Improving Performance of All-Polymer Solar Cells Through Backbone Engineering of Both Donors and Acceptors

All-polymer solar cells (APSCs), composed of semiconducting donor and acceptor polymers, have attracted considerable attention due to their unique advantages compared to polymer-fullerene-based devices in terms of enhanced light absorption and morphological stability. To improve the performance of APSCs, the morphology of the active layer must be optimized. By employing a random copolymerization strategy to control the regularity of the backbone of the donor polymers (PTAZ-TPDx) and acceptor polymers (PNDI-Tx) the morphology can be systematically optimized by tuning the polymer packing and crystallinity. To minimize effects of molecular weight, both donor and acceptor polymers have number-average molecular weights in narrow ranges. Experimental and coarse-grained modeling results disclose that systematic backbone engineering greatly affects the polymer crystallinity and ultimately the phase separation and morphology of the all-polymer blends. Decreasing the backbone regularity of either the donor or the acceptor polymer reduces the local crystallinity of the individual phase in blend films, affording reduced short-circuit current densities and fill factors. This two-dimensional crystallinity optimization strategy locates a PCE maximum at highest crystallinity for both donor and acceptor polymers. Overall, this study demonstrates that proper control of both donor and acceptor polymer crystallinity simultaneously is essential to optimize APSC performance

Developing Composite Insulating Cross-Arms for 400 kV Lattice Towers

\u3cp\u3ePolymorphism of organic semiconducting materials exerts critical effects on their physical properties such as optical absorption, emission and electrical conductivity, and provides an excellent platform for investigating structure–property relations. It is, however, challenging to efficiently tune the polymorphism of conjugated polymers in aggregated, semi-crystalline phases due to their conformational freedom and anisotropic nature. Here, two distinctly different semi-crystalline polymorphs (β\u3csub\u3e1\u3c/sub\u3e and β\u3csub\u3e2\u3c/sub\u3e) of a low-bandgap diketopyrrolopyrrole polymer are formed through controlling the solvent quality, as evidenced by spectroscopic, structural, thermal and charge transport studies. Compared to β\u3csub\u3e1\u3c/sub\u3e, the β\u3csub\u3e2\u3c/sub\u3e polymorph exhibits a lower optical band gap, an enhanced photoluminescence, a reduced π-stacking distance, a higher hole mobility in field-effect transistors and improved photocurrent generation in polymer solar cells. The β\u3csub\u3e1\u3c/sub\u3e and β\u3csub\u3e2\u3c/sub\u3e polymorphs provide insights into the control of polymer self-organization for plastic electronics and hold potential for developing programmable ink formulations for next-generation electronic devices.\u3c/p\u3

Effects of Particulate Air Pollution on Cardiovascular Health: A Population Health Risk Assessment

Particulate matter (PM) air pollution is increasingly recognized as an important and modifiable risk factor for adverse health outcomes including cardiovascular disease (CVD). However, there are still gaps regarding large population risk assessment. Results from the nationwide Behavioral Risk Factor Surveillance System (BRFSS) were used along with air quality monitoring measurements to implement a systematic evaluation of PM-related CVD risks at the national and regional scales. CVD status and individual-level risk factors were collected from more than 500,000 BRFSS respondents across 2,231 contiguous U.S. counties for 2007 and 2009. Chronic exposures to PM pollutants were estimated with spatial modeling from measurement data. CVD outcomes attributable to PM pollutants were assessed by mixed-effects logistic regression and latent class regression (LCR), with adjustment for multicausality. There were positive associations between CVD and PM after accounting for competing risk factors: the multivariable-adjusted odds for the multiplicity of CVD outcomes increased by 1.32 (95% confidence interval: 1.23–1.43) and 1.15 (1.07–1.22) times per 10 µg/m3 increase in PM2.5 and PM10 respectively in the LCR analyses. After controlling for spatial confounding, there were moderate estimated effects of PM exposure on multiple cardiovascular manifestations. These results suggest that chronic exposures to ambient particulates are important environmental risk factors for cardiovascular morbidity