Search

It is of great concern to reduce greenhouse gases (GHG) and ammonia (NH3) emissions from animal manure composting in China. The purpose of this study was to investigate effects of adding red mud on emissions of GHG (methane (CH4), nitrous oxide (N2O)) and NH3 in full-scale swine manure windrow composting. Two full-scale swine manure windrow composting experiments were carried out to compare emission of GHG and NH3 with and without addition of red mud. Results showed that the addition of modified red mud reduced N2O emissions by 4.03%, however, it did not help reduce CH4 emissions (51.65% higher than that of the control test). Ammonia emission from both the experimental and the control tests were similar. The addition of modified red mud was useful to conserve nitrogen and phosphorus because the contents of total nitrogen and total phosphorus in the compost of the experiment test were higher than the control test. It was also found that turning was useful to reduce CH4 emissions, i.e. 51.72% reduction of CH4 emission after turning compared to before turning. However, turning resulted in an increased N2O emission flux by 23.15 times in the experiment test and 15.31 times in the control test, respectively.

Forest ecosystems provide a variety of services and forest ecosystem man- agement (FEM) is an effective approach to maximize the services. Because of the com- plexity of forest ecosystems, the applications of FEM can be facilitated with decision support systems (DSS) that recognize and incorporate ecological and socio-economic variables. With the rapid development of computation and information technologies, DSS have been advanced in many ways. Traditional forest management within a forestry unit in China is planned on a yearly basis. The planning itself remains primarily a verbal concept as there are no quantitative decision-support tools available to translate the concept into forest management actions. For the purposes of FEM at the management level, a forest management DFF, FORESTAR ® , has been developed under a framework of geographic information system (GIS) and forest models. The paper explained the intelligent modeling mechanisms and demonstrated how the applications of FEM can be strengthened with the applications of FORESTAR ® .