Carbon （C） sequestration through plantations is one of the important mitigation measures for rising levels of carbon dioxide and other greenhouse gases in the atmosphere. This study aimed to assess C stocks and thei...Carbon （C） sequestration through plantations is one of the important mitigation measures for rising levels of carbon dioxide and other greenhouse gases in the atmosphere. This study aimed to assess C stocks and their sequestration rate, and to develop allometric models for estimation of C stocking in age-series young teak （Tectona grandis） planta- tions （1, 5, 11, 18, 24 and 30 years） by using biomass and productivity estimation and regression, respectively. These plantations were raised in tropical moist deciduous forests of Kumaun Himalayan tarai. Total C stocks estimated for these plantations were 1.6, 15.8, 35.4, 39.0, 61.5 and 73.2 Mg ha-1, respectively. Aboveground and belowground C storage in- creased with increasing plantation age; however, the range of their percentage contribution showed little variation （87.8-88.2 and 11.7-12.7 %, respectively）, The rate of C sequestration for these respective plantations was 1.06, 6.95, 5.46, 5.42, 3.39 and 5.37 Mg ha-1 a-1. Forty percent of the aboveground annual storage was retained in the tree while 60 % was released in the form of foliage, twigs, and fruit litter. In the case of total （tree） annual production, 43 % was retained while 57 % was released as litter including root. C stock, C sequestration rate, accumulation ratio （1.4-18.1）, root：shoot C ratio （0.61--0.13） and production efficiency （0.01-0.18） were comparable to some previous reports for other species and forests. These data could be useful in deciding the harvesting age for young teak with respect to C storage and sequestrationrate. Four allometric models using linear regression equations were developed between biomass （twice the C stock） and diameter, girth, and height of the tree at different ages. The diameter model was found more suitable for C stock predic- tion in similar areas.展开更多
Based on the data of MSW generation in Beijing from 2004 to 2012,an ARIMA model of time series analysis was established. By contrast of the modeling results of different yearly data,the forecast period was identified ...Based on the data of MSW generation in Beijing from 2004 to 2012,an ARIMA model of time series analysis was established. By contrast of the modeling results of different yearly data,the forecast period was identified to be 10 years. The yearly production of MSW from 2015 to 2025 was forecasted by using SPSS 16. 0 software. Result shows that the forecasting effect of ARIMA( 1,0,1) model is relatively good,and it can be applied to prediction of MSW production in Beijing. In the next 10 years,the amount of MSW produced in Beijing is increasing,but the growth rate is not large. Is expected to 2025,the production of MSW will reach more than 9 million tons. Taking into account the MSW return,it is inferred that the production of MSW in Beijing in 2025 will be close to 10 million tons. In order to reduce the pressure of subsequent waste disposal facilities in Beijing,the government can increase the intensity of the recycling of waste materials.展开更多
Industrial production series are volatile and often cyclical. Time series models can be used toestablish certain stylized facts, such as trends and cycles, which may be present in these series. Incertain situations, ... Industrial production series are volatile and often cyclical. Time series models can be used toestablish certain stylized facts, such as trends and cycles, which may be present in these series. Incertain situations, it is also possible that common factors, which may have an interesting interpretation,can be detected in production series. Series from two neighboring countries with close economicrelationships, such as Germany and Austria, are especially likely to exhibit such joint stylized facts.展开更多
Based on the annual sample data on food production in China since the reform and opening up,we select 8 main factors influencing the total food production( growing area,application rate of chemical fertilizer,effectiv...Based on the annual sample data on food production in China since the reform and opening up,we select 8 main factors influencing the total food production( growing area,application rate of chemical fertilizer,effective irrigation area,the affected area,total machinery power,food production cost index,food production price index,financial funds for supporting agriculture,farmers and countryside),and put them into categories of material input,resources and environment,and policy factors. Using the factor analysis,we carry out the multi-angle analysis of these typical influencing factors one by one through the time series trend chart. It is found that application rate of chemical fertilizer,the growing area of food crops and drought-affected area become the key factors affecting food production. On this basis,we set forth the corresponding recommendations for improving the comprehensive food production capacity.展开更多
文摘Carbon （C） sequestration through plantations is one of the important mitigation measures for rising levels of carbon dioxide and other greenhouse gases in the atmosphere. This study aimed to assess C stocks and their sequestration rate, and to develop allometric models for estimation of C stocking in age-series young teak （Tectona grandis） planta- tions （1, 5, 11, 18, 24 and 30 years） by using biomass and productivity estimation and regression, respectively. These plantations were raised in tropical moist deciduous forests of Kumaun Himalayan tarai. Total C stocks estimated for these plantations were 1.6, 15.8, 35.4, 39.0, 61.5 and 73.2 Mg ha-1, respectively. Aboveground and belowground C storage in- creased with increasing plantation age; however, the range of their percentage contribution showed little variation （87.8-88.2 and 11.7-12.7 %, respectively）, The rate of C sequestration for these respective plantations was 1.06, 6.95, 5.46, 5.42, 3.39 and 5.37 Mg ha-1 a-1. Forty percent of the aboveground annual storage was retained in the tree while 60 % was released in the form of foliage, twigs, and fruit litter. In the case of total （tree） annual production, 43 % was retained while 57 % was released as litter including root. C stock, C sequestration rate, accumulation ratio （1.4-18.1）, root：shoot C ratio （0.61--0.13） and production efficiency （0.01-0.18） were comparable to some previous reports for other species and forests. These data could be useful in deciding the harvesting age for young teak with respect to C storage and sequestrationrate. Four allometric models using linear regression equations were developed between biomass （twice the C stock） and diameter, girth, and height of the tree at different ages. The diameter model was found more suitable for C stock predic- tion in similar areas.
基金Supported by the Project of Beijing Municipal Commission of City Management(SC1708A)
文摘Based on the data of MSW generation in Beijing from 2004 to 2012,an ARIMA model of time series analysis was established. By contrast of the modeling results of different yearly data,the forecast period was identified to be 10 years. The yearly production of MSW from 2015 to 2025 was forecasted by using SPSS 16. 0 software. Result shows that the forecasting effect of ARIMA( 1,0,1) model is relatively good,and it can be applied to prediction of MSW production in Beijing. In the next 10 years,the amount of MSW produced in Beijing is increasing,but the growth rate is not large. Is expected to 2025,the production of MSW will reach more than 9 million tons. Taking into account the MSW return,it is inferred that the production of MSW in Beijing in 2025 will be close to 10 million tons. In order to reduce the pressure of subsequent waste disposal facilities in Beijing,the government can increase the intensity of the recycling of waste materials.
文摘 Industrial production series are volatile and often cyclical. Time series models can be used toestablish certain stylized facts, such as trends and cycles, which may be present in these series. Incertain situations, it is also possible that common factors, which may have an interesting interpretation,can be detected in production series. Series from two neighboring countries with close economicrelationships, such as Germany and Austria, are especially likely to exhibit such joint stylized facts.
基金Supported by Humanities and Social Sciences Fund of the Ministry of Education(12YJC790094)Tianjin Philosophy and Social Science Planning Project(TJYY13-028TJLJ13-011)
文摘Based on the annual sample data on food production in China since the reform and opening up,we select 8 main factors influencing the total food production( growing area,application rate of chemical fertilizer,effective irrigation area,the affected area,total machinery power,food production cost index,food production price index,financial funds for supporting agriculture,farmers and countryside),and put them into categories of material input,resources and environment,and policy factors. Using the factor analysis,we carry out the multi-angle analysis of these typical influencing factors one by one through the time series trend chart. It is found that application rate of chemical fertilizer,the growing area of food crops and drought-affected area become the key factors affecting food production. On this basis,we set forth the corresponding recommendations for improving the comprehensive food production capacity.
