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Xiao H.,Hunan Normal University | Liu H.-N.,Hunan Normal University | Gao L.-D.,U.S. Center for Disease Control and Prevention | Huang C.-R.,Griffith University | And 5 more authors.
PLoS ONE | Year: 2013

Background: The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by population dynamics of its main host, rodents. It is therefore important to better understand rodents' characteristic in epidemic areas. Methodology/Principal Findings: We examined the potential impact of food available and climatic variability on HFRS rodent host and developed forecasting models. Monthly rodent density of HFRS host and climate data in Changsha from January 2004 to December 2011 were obtained. Monthly normalized difference vegetation index (NDVI) and temperature vegetation dryness index (TVDI) for rice paddies were extracted from MODIS data. Cross-correlation analysis were carried out to explore correlation between climatic variables and food available with monthly rodent data. We used auto-regressive integrated moving average model with explanatory variables to examine the independent contribution of climatic variables and food supply to rodent density. The results indicated that relative rodent density of HFRS host was significantly correlated with monthly mean temperatures, monthly accumulative precipitation, TVDI and NDVI with lags of 1-6 months. Conclusions/Significance: Food available plays a significant role in population fluctuations of HFRS host in Changsha. The model developed in this study has implications for HFRS control and prevention. © 2013 Xiao et al. Source


Fang X.,Beijing Jiaotong University | Jia L.,Beijing Jiaotong University | Tan Z.,Beijing Jiaotong University | Wang Z.,Beijing Energy Conservation and Environmental Protection Center
Beijing Jiaotong Daxue Xuebao/Journal of Beijing Jiaotong University | Year: 2012

Effects of heating rate, oxygen concentration and water concentration on biomass combustion were investigated by themogravimetric analyzer. It is found that thermal hysteresis occurs and ignition tends to occur in particle surface when heating rate is too high, and the combustion characteristic temperature, mass loss rate and the percentage of residual mass are all affected. With the increasing of oxygen concentration, mass transfer of oxygen to the solid layer is strengthened, making the volatile matters and solid layer burn simultaneously and resulting in a larger burning rate but a lower burnout temperature. Moisture concentration in humid air affects the biomass combustion. The combustion instability is due to condensation and evaporation of water, which cause fluctuation of heat load in the furnace. Source


Li Z.,Beijing Normal University | Li Z.,Beijing Energy Conservation and Environmental Protection Center | Li X.Y.,Beijing Normal University | Sun J.,Chinese Research Academy of Environmental Sciences
Applied Mechanics and Materials | Year: 2013

Climate is an important factor which formed and affected surface water resources. Through sensitivity analysis of natural runoff towards climate change, assuming the main factors effect runoff are precipitation and temperature, then according to the possible tendency of climate changes in the future, set climate scenarios, and use the hydrological model simulate the changes trend of runoff under different climate scenarios, thereby analyze the climate change impacts on surface water resources. The results show that annual runoff will be increased with the increasing annual precipitation, and it will be reduced with rise of annual temperature, the sensitivity that annual runoff towards the change of precipitation and temperature are equally notable, both of them are two major factors impact on the change of runoff and the precipitation change impacts on annual runoff will be even more obvious in flood season. Last, with the global warming trend, put forward the corresponding adaptive measures of energy conservation and emissions reduction. © (2013) Trans Tech Publications, Switzerland. Source


Li M.,Chinese Academy of Agricultural Sciences | Li M.,Key Laboratory of Farm Building in Structure and Construction | Zhou C.,Chinese Academy of Agricultural Sciences | Zhou C.,Key Laboratory of Farm Building in Structure and Construction | And 7 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2016

Soil wall of the Chinese solar greenhouse (hereafter referred to as "solar greenhouse") has problems of occupying large area and damaging the cultivation land. The simplification of soil wall, which means decreasing the thickness and soil use of the soil wall, becomes very important. The purpose of this study is to develop simplification methods of soil wall. A simplification wall with less soil use was proposed based on the measured temperature of soil wall and analysis of feasibility of those methods. The tested solar greenhouse was located in Yongqing county, Lanfang city, Hebei province (116°44' E, 36°27' N). It is 50 m long and 10 m wide. The top and bottom thicknesses of the soil wall were 2.0 and 5.3 m, respectively. Its average thickness was 3.6 m. The test period was from Dec. 01, 2013 to Mar. 30, 2014. During that time, the tested solar greenhouse was used to growing cucumber with surface irrigation. The heat insulation sheet of the solar greenhouse was rolled up and down at 8:30 am and 5:00 pm daily, respectively. The wind vent was open if the indoor air temperature was high during daytime. The indoor and outdoor air temperatures, solar irradiating on the inner surface of the wall, the temperatures in the soil wall and indoor soil were measured continuously at a time interval of 10 min. The data collected in a typical cloudy day ( 08:30 am of Dec. 29, 2013 to 08:30 am of Dec. 30, 2013) and a typical sunny day (08:30 am of Jan. 16, 2014 to 08:30 am of Jan. 17, 2014) were used to study the heat transfer pattern of the soil wall. Based on the measured temperature in the soil wall, the soil wall can be divided into heat storage layer and heat insulation layer. The heat storage layer had large temperature fluctuation and can be used for storing heat during daytime and release heat into the solar greenhouse during nighttime. The temperature of the heat insulation layer was lower than that of the heat storage layer and mainly used to prevent the heat in the heat storage layer from losing. Under the test conditions, the thicknesses of heat storage and insulation layers were 47 cm and 313 cm, respectively. Considering that the heat resistance of the heat insulation layer equals that of 7 cm polystyrene board, a composite wall with 7 cm polystyrene board and 47 cm rammed soil in the direction from exterior to interior was proposed. The results showed that under same conditions, the differences between the measured inner surface temperature of the soil wall and the simulated inner surface temperature of the composite wall was less than 5% in both sunny and cloudy days. The application of the polystyrene board can reduce the thickness and occupied area of soil wall by 85.0% and 89.8%, respectively in comparison with the conventional soil wall. On the other hand, the heats released by the indoor soil during the nights of sunny and cloudy day were 1.3 and 2.9 times more compared to those released by the soil wall. According to the simulation results, by increasing the 20 cm surface soil temperature from 17.0℃ to 23℃, the heat released by the indoor soil during nighttime were more than the measured heat released by both soil wall and indoor soil. In this case, the soil wall can be replaced by the wall build with thermal insulation material only. The thickness of soil wall can be further decreased. We concluded that the soil wall can be simplified by the following methods: 1) building its heat insulation layer with thermal insulation material, or 2) building the wall with thermal insulation material and increasing the indoor soil temperature. © 2016, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved. Source


Chen C.,North China Electrical Power University | Huang G.,North China Electrical Power University | Li Y.,North China Electrical Power University | Li M.,Beijing Energy Conservation and Environmental Protection Center
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2013

The transport cost of biomass fuels accounts for a large proportion of the total cost of the operation of biomass power plant. Optimizing biomass power plant site can largely mitigate the transport cost and reduce the pollutant emissions from the transportation process of biomass fuels. Therefore, it is significant to optimize the biomass power plant sit. However, the biomass power system contains many uncertainties, because that many parameters can hardly be acquired as deterministic values but expressed as interval and/or stochastic formats. For example, the supply demand of biomass fuels can be expressed as probability distributions; also, interval values can describe the uncertain parameters such as the biomass fuels price, which fluctuates between lower and upper bounds. Energy systems would become insecurity and with a high risk without considering these uncertainties. Security is a priority in the operation of biomass power plant. In this study, a stochastic robust interval model (SRIM) was developed for the biomass power plant site selection under uncertainties, through incorporating interval-parameter programming (IPP) and robust optimization (RO) within two-stage programming (TSP) framework. In SRIM, decision variables were divided into two subsets: those that must be determined before the realizations of random variables were known, and those that were determined after the realized random variables were available. The SRIM can deal with the uncertainties described in the terms of the interval values and probability distributions, moreover, it can also reflect economic penalties as corrective measures or recourse against any infeasibilities arising due to a particular realization of an uncertain event. In the SRIM modeling formulation, penalties were exercised with the recourse against any infeasibility, and robustness measures were introduced to examine the variability of the second stage costs that were above the expected levels. The SRIM was generally suitable for risk-aversive planners under high-variability conditions. The SRIM method was applied to a hypothetical case of planning biomass power plant (with installed capacity of 15 MW) site selection with considering the uncertainties. A number of solutions under different robustness levels have been generated. The obtained results can help generate desired decision alternatives that will be able to enhance the safety of biomass power system with a low system-failure risk level and particularly useful for risk-aversive decision makers in handling high-variability conditions. The result are beneficial for managers analyzing the results to gain insights into the tradeoff between system's safety and economic, and analyzing the risk of the system. The results of SRIM shows: 1) The construction number of biomass power plant is one; 2) The optimum biomass power plant is from (245, 242) km to (250, 247) km; 3) The optimum allocation scheme for each fuel purchase and storage station; 4) The system costs under different robust levels; 5) The notion of risk in stochastic programming under different robust levels. The modeling results from the RISO can help generate desired decision alternatives that will be able to not only enhance the safety of planning biomass power plant site selection with a low system-failure risk level, but also mitigate pollutant emissions from the transportation process of biomass fuels. The results are reasonable, and could provide a reference for the selection of the biomass power plant site. Source

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