Adoption and sustained use of improved cookstoves

The adoption and sustained use of improved cookstoves are critical performance parameters of the cooking system that must be monitored just like the rest of the stove technical requirements to ensure the sustainability of their benefits. No stove program can achieve its goals unless people initially accept the stoves and continue using them on a long-term basis. When a new stove is brought into a household, commonly a stacking of stoves and fuels takes place with each device being used for the cooking practices where it fits best. Therefore, to better understand the adoption process and assess the impacts of introducing a new stove it is necessary to examine the relative advantages of each device in terms of each of the main cooking practices and available fuels. An emerging generation of sensor-based tools is making possible continuous and objective monitoring of the stove adoption process (from acceptance to sustained use or disadoption), and has enabled its scalability. Such monitoring is also needed for transparent verification in carbon projects and for improved dissemination by strategically targeting the users with the highest adoption potential and the substitution of cooking practices with the highest indoor air pollution or greenhouse gas contributions.     

Optimal design of air-conditioning systems using deep seawater

Clean Technologies and Environmental Policy - This paper presents a multi-objective mixed integer linear programming problem for the optimization of seawater air-conditioning systems using deep...     

Influence of manganese and ammonium oxidation on the removal of 17 alpha-ethinylestradiol (EE2)

Flow-through reactors with manganese oxides were examined for their capacity to remove 17α-ethinylestradiol (EE2) at μg L⁻¹ and ng L⁻¹ range from synthetic wastewater treatment plant (WWTP) effluent. The mineral MnO₂ reactors removed 93% at a volumetric loading rate (B_V) of 5 μg EE2 L⁻¹ d⁻¹ and from a B_V of 40 μg EE2 L⁻¹ d⁻¹ on, these reactors showed 75% EE2 removal. With the biologically produced manganese oxides, only 57% EE2 was removed at 40 μg EE2 L⁻¹ d⁻¹. EE2 removal in the ng L⁻¹ range was 84%. The ammonium present in the influent (10 mg N L⁻¹) was nitrified and ammonia-oxidizing bacteria (AOB) were found to be of prime importance for the degradation of EE2. Remarkably, EE2 removal by AOB continued for a period of 4 months after depleting NH₄⁺ in the influent. EE2 removal by manganese-oxidizing bacteria was inhibited by NH₄⁺. These results indicate that the metabolic properties of nitrifiers can be employed to polish water containing EE2 based estrogenic activity.     

Effect of Initial Headspace O2 Level on the Growth and Volatile Metabolite Production of Leuconostoc Mesenteriodes and the Microbial and Sensorial Quality of Modified Atmosphere Packaged Par‐Fried French Fries

This study evaluated the effect of residual O₂ level (0% to 5%) on microbial growth and volatile metabolite production on par‐fried French fries packaged in a modified atmosphere with 60% CO₂ (rest N₂) at 4 °C. The results obtained showed that the initial headspace (IH) O₂ level had an effect on growth of Leuconostoc mesenteroides on French fry simulation agar, whereby growth was slightly faster under 5% O₂. In terms of quantity, ethanol, 2‐methyl‐1‐propanol, and dimethyl disulphide were the most significant volatile metabolites produced by L. mesenteroides. The production of ethanol by L. mesenteroides was highest on simulation agar packaged under low IH O₂ levels (0% to 1%), indicating that the fermentative metabolism was induced under these conditions. In agreement with the results observed on the simulation medium, growth of native lactic acid bacteria was faster under an IH O₂ level of 5%. In addition, ethanol, 2‐methyl‐1‐propanol, and dimethyl disulphide were also quantitatively the most important volatile metabolites. However, in contrast, greater quantities of ethanol and dimethyl disulphide were produced on par‐fried French fries packaged under 5% O₂. This was attributed to the limited growth of the native flora on the par‐fried French fries under residual O₂ levels of 0% and 1%. Although some significant differences (P < 0.05) occurred between the French fries packaged in 0%, 1%, and 5 % residual O₂ during storage, all products were considered to be acceptable for consumption. The results of this study can be used to optimize the shelf‐life of packaged chill stored potato products.     

The peripheral viewing of dials.

Four Ss each read dials of four pointer designs at lateral displacements of 10° from 10° to 80°. Results were analyzed in terms of time and error scores. No significant differences were found among the pointer designs. "If reversal errors are ignored, the ability to discriminate pointer position when the dial is displaced as much as 40° from the fixation point is good. Even at 80°… readings are better than chance." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Linearization of the activated sludge model ASM1 for fast and reliable predictions

In this paper a strategy is proposed to reduce the complexity of the activated sludge model no. 1 (ASM1) which describes the biotransformation processes in a common activated sludge process with N-removal. The key feature of the obtained reduced model is that it combines high predictive value (all state variables keep their biological interpretation) with very low computation time. Therefore, this model is a valuable tool in a risk assessment environment (designed for the evaluation of wastewater treatment plants facing stricter effluent norms) as well as in on-line (MPC) control strategies. The complexity reduction procedure consists of four steps. In the first step representative input/output data sets are generated by simulating the full ASM1 model. In the second step the ASM1 model is rewritten in state space format with linear approximations of the nonlinear (kinetic) terms. In the third step the unknown parameters in the linear terms are identified based on the generated input/output data. To reduce the amount of parameter sets that have to be identified (to cover the full operation range of the plant), a Multi-Model interpolation procedure is introduced as a last step.