Fate and availability of glyphosate and AMPA in agricultural soil

The fate of glyphosate and its degradation product aminomethylphosphonic acid (AMPA) was studied in soil. Labeled glyphosate was used to be able to distinguish the measured quantities of glyphosate and AMPA from the background values since the soil was sampled in a field where glyphosate had been used formerly. After addition of labeled glyphosate, the disappearance of glyphosate and the formation and disappearance of AMPA were monitored. The resulting curves were fitted according to a new EU guideline. The best fit of the glyphosate degradation data was obtained using a first-order multi compartment (FOMC) model. DT₅₀ values of 9 days (glyphosate) and 32 days (AMPA) indicated relatively rapid degradation. After an aging period of 6 months, the leaching risk of each residue was determined by treating the soil with pure water or a phosphate solution (pH 6), to simulate rain over a non-fertilized or fertilized field, respectively. Significantly larger (p < 0.05) amounts of aged glyphosate and AMPA were extracted from the soil when phosphate solution was used as an extraction agent, compared with pure water. This indicates that the risk of leaching of aged glyphosate and AMPA residues from soil is greater in fertilized soil. The blank soil, to which 252 g glyphosate/ha was applied 21 months before this study, contained 0.81 ng glyphosate/g dry soil and 10.46 ng AMPA/g dry soil at the start of the study. Blank soil samples were used as controls without glyphosate addition. After incubation of the blank soil samples for 6 months, a significantly larger amount of AMPA was extracted from the soil treated with phosphate solution than from that treated with pure water. To determine the degree of uptake of aged glyphosate residues by crops growing in the soil, ¹⁴C-labeled glyphosate was applied to soil 6.5 months prior to sowing rape and barley seeds. After 41 days, 0.006 ± 0.002% and 0.005 ± 0.001% of the applied radioactivity was measured in rape and barley, respectively.     

企业参与对CDM环境效力影响研究

扩大企业对CDM的参与是提高清洁发展机制减排效果的关键因素，但是随着参与的不断扩大，可能产生价格因素、小项目开发障碍、“普遍性”等阻碍因素，将影响企业对CDM参与性的继续扩大，对减排效果的提高造成负面影响。在对企业参与和CDM环境效力相互关系探讨的基础上，本文对如何继续扩大参与、加大减排提出了发展建议。     

Using supercritical carbon dioxide as solvent to replace water in polyethylene terephthalate (PET) fabric dyeing procedures

Dyeing fabrics in supercritical carbon dioxide (SCD) instead of water can save energy, reduce water use and prevent pollution. The special pilot plant was designed to test dyeing procedures in supercritical carbon dioxide and the analyses of the results indicate major benefits as compared to water based procedures. The dyeing of polyethylene terephthalate (PET) fabric in supercritical carbon dioxide using special pilot plant was investigated. Disperse dye, C.I. (color index) Disperse Blue 79, was used in this study. After dyeing, rinsing in supercritical carbon dioxide, which removes the excess dyes, was also discussed. At the same dyeing conditions, K/S (color yield) of dyed fabric significantly increased with increasing the dye concentration from 1% o.w.f. (on weight of fabric) to 5% o.w.f. Dyeing temperature and pressure had a strong influence on the color yield. When the temperature rose above 110 °C, the increase in color yield was obvious. At 20 MPa, 120–130 °C, dyeing reached equilibrium after 60 min. The excess dye of the dyed PET fabric was small. The suitable condition in supercritical carbon dioxide for removal of excess dye from the dyed fabric was 70 °C, 20 MPa. The PET fabric dyed in supercritical carbon dioxide had good fastness and physical properties.     

Conserving water by optimizing production schedules in the dyeing industry

Industrial dyeing processes generate a huge amount of wastewater, because the production lines have to be washed out each time when the dye changes. We propose an algorithm for the optimization of production schedule. It aims to reduce the production time and the amount of freshwater consumption by optimization the groups orders according to color. Furthermore, we develop software based on the genetic algorithm and implement it in a Chinese company. We optimize the schedules in three months of the case company and compare its output to actual data. The results show that compared to the original manual schedules, the optimized schedules cut production time by 10–15%, reduce freshwater consumption by 20–30%, and reduce wastewater generation by about 20%.