Estimating contribution of wildland fires to ambient ozone levels in National Parks in the Sierra Nevada, California

Data from four continuous ozone and weather monitoring sites operated by the National Park Service in Sierra Nevada, California, are used to develop an ozone forecasting model and to estimate the contribution of wildland fires on ambient ozone levels. The analyses of weather and ozone data pointed to the transport of ozone precursors from the Central Valley as an important source of pollution in these National Parks. Comparisons of forecasted and observed values demonstrated that accurate forecasts of next-day hourly ozone levels may be achieved by using a time series model with historic averages, expected local weather and modeled PM values as explanatory variables. Results on fire smoke influence indicated occurrence of significant increases in average ozone levels with increasing fire activity. The overall effect on diurnal ozone values, however, was small when compared with the amount of variability attributed to sources other than fire.     

时间序列模型在火警短期预测中的应用

基于某市的119火警数据,采用时间序列模型中的ARIMA算法进行了分析.计算结果表明,该市119火警数据的天序列服从ARIMA(0,1,2)模型,周序列服从ARIMA(1,0,0)模型.从模型对数据的拟合效果来看,ARIMA模型较为准确的反映了数据序列的发展趋势.采用这两种模型对数据序列分别进行了短期的预测,其预测值与实际结果在趋势上基本一致,研究表明采用周序列预测的效果要好于天序列.基于时序模型的火警预测方法是实现时火灾应急处置中关口前移的重要措施.     

Municipal solid waste production and composition in Finland—Changes in the period 1960–2002 and prospects until 2020

Waste reduction was recognised as the main goal of waste management policy in the EU in the 1990s. Although knowledge of past waste generation is essential for effective waste reduction policy there are no comprehensive statistics on the past development of municipal solid waste (MSW) production. MSW management is currently under turmoil in many EU countries as the requirements of the EC landfill directive (1999/31/EC) are set into force. In this study, the production and composition of MSW in Finland between 1960 and 2002 is presented using historical data. The impact of population, affluence and technology on MSW production are analysed using the IPAT equation and three scenarios are constructed until year 2020. The results are compared with national future targets on MSW production. Production of MSW increased in Finland until 1990, declined to year 1997, increased to 2000 and then declined again. The share of organic and plastic waste increased over the study period while the share of paper and cardboard declined. The results suggest that so far national targets on MSW reduction have been set fairly low. Moreover, our scenarios depict a wide range of future MSW production, even though the time horizon is not longer than 15 years into the future. In order to narrow this range, continuous improvement of the statistics of MSW is essential.     

Individual changes in human EEG caused by 450 MHz microwave modulated at 40 and 70 Hz

This study was aimed to investigate the changes in the human electroencephalographic (EEG) signal caused by modulated low-level microwaves. The 450 MHz microwave exposure modulated at 40 Hz and 70 Hz frequencies was applied to a group of 15 volunteers. The field power density at the scalp was 0.16 mW/cm². Ten cycles of the exposure (1 min on and 1 min off) at both modulation frequencies were applied. Analysis of the EEG signal was performed using three different methods: nonlinear method of scaling analysis for length distribution of low variability periods (LDLVP), relative changes in EEG energy (S-parameter) and beta ratio (H-parameter). The analysis revealed significant changes caused by microwave for the whole group (H-parameter method). The exposure caused increase of the EEG beta power (S-parameter method). Statistically significant changes in EEG were detected for four subjects (26.7%) at 40 Hz modulation frequency (LDLVP method).     

时变条件下的有害物品运输的人口风险分析

随着工业的发展 ,有害物品运输量在逐年增加 ,有害物品对于人类威胁也在加大 ,有害物品运输的风险问题受到了广泛的关注。由于有害物品运输中 ,路径周围的人口密度随着时间的变化而变化 ,进而影响在运输过程中的人口风险。笔者在有时变情况下 ,对有害物品运输人口风险进行了分析 ;建立了估计人口风险的模型 ;获得了有害物品运输中的最小人口风险以及最佳出发时间 ;进一步完善了有害物品的运输的风险分析 ;为如何减少有害物品运输的人口风险提供了依据。     

The Time Invariance Principle,the absence of ecological chaos,and a fundamental pitfall of discrete modeling

This paper is to show that most discrete models used for population dynamics in ecology are inherently pathological that their predications cannot be independently verified by experiments because they violate a fundamental principle of physics. The result is used to tackle an on-going controversy regarding ecological chaos. Another implication of the result is that all dynamical systems must be modeled by differential equations. As a result it suggests that researches based on discrete modeling must be closely scrutinized and the teaching of calculus and differential equations must be emphasized for students of biology.     

Fish forewarning of comprehensive toxicity in water environment based on Bayesian sequential method

Environmental impact of pollutants can be analyzed effectively by acquiring fish behavioral signals in water with biological behavior sensors. However, a variety of factors, such as the complexity of biological organisms themselves, the device error and the environmental noise, may compromise the accuracy and timeliness of model predictions. The current methods lack prior knowledge about the fish behavioral signals corresponding to characteristic pollutants, and in the event of a pollutant invasion, the fish behavioral signals are poorly discriminated. Therefore, we propose a novel method based on Bayesian sequential, which utilizes multi-channel prior knowledge to calculate the outlier sequence based on wavelet feature followed by calculating the anomaly probability of observed values. Furthermore, the relationship between the anomaly probability and toxicity is analyzed in order to achieve forewarning effectively. At last, our algorithm for fish toxicity detection is verified by integrating the data on laboratory acceptance of characteristic pollutants. The results show that only one false positive occurred in the six experiments, the present algorithm is effective in suppressing false positives and negatives, which increases the reliability of toxicity detections, and thereby has certain applicability and universality in engineering applications.     

Benefits, efforts and risks of participants in landscape co-management: an analytical framework and results from two case studies in Austria

Participatory processes in general and also in relation to managing landscape issues are gathering importance mostly due to arguments surrounding legitimacy and effectiveness in decision-making. The main aim of this research, based on a transaction costs perspective, is to present an integrated analytical framework in order to determine individual efforts (time, money), benefits and risks of participants in landscape co-management processes. Furthermore a reflection on the analytical approach developed and arising lessons to be learned for landscape co-management are presented. In the analytical framework benefit-components comprise of factors such as 'contributing to landscape maintenance/development and nature protection', 'representing one's interest group', 'co-deciding on relevant topics', 'providing and broadening one's knowledge' and 'building networks'. The risks of participation are related to a lack of information and agreements, missing support and actual decision-making power. The analytical framework is applied to two case studies in Austria: an EU LIFE-Nature project and a Cultural Landscape Project of the Provincial Government of Lower Austria. Analysis of the effort-benefit-relations provides an indication for a more effective design of co-management. Although the processes are rated as quite adequate, there is a low willingness of participants to commit additional time to co-management processes. In contrast to the Cultural Landscape Project, in the LIFE-Nature project, professionally involved persons participate next to partly and full volunteers. These uneven conditions of participation and an unfair distribution of transaction costs, jeopardize the promising chances co-management bears for landscape governance.     

季节调整分析在城市火灾发生规律研究中的应用

利用样本周期图法定量分析了城市火灾序列的周期性,并实例分析得出了北京市火灾时间序列具有12个月和48个月的周期性。然后采用季节调整法,将火灾时间序列中的季节因子和不规则因子提取出来,得出了经季节调整后的时间序列,从而得到了北京市火灾发生受季节因素影响的大小和城市火灾时间序列的基本发展趋势,大大提高了火灾数据之间的可比性。同时结论可为消防管理部门有针对性地采取消防监督管理措施和科学地安排消防执勤战备提供有力指导。     

两种应用场景下NDVI时间序列数据拟合方法研究

植被覆盖指数（NDVI）时间序列数据集包含地表植被的长势、生长周期、时空变化等信息,其拟合重建结果可应用于物候信息提取、生态质量评价、人类活动扰动识别、覆被变化动态监测等方面。基于TIMESAT软件,选取物候参数提取和扰动识别2个应用场景,结合地面站点数据和Jacknife法模拟数据,对比分析非对称高斯函数拟合法（AG法）、双Logistic函数拟合法（D-L法）和Savitzky-Golay滤波法（S-G法）3种方法的拟合效果。结果表明：（1）3种方法拟合重建后提取的生长开始时间（SOS）、生长结束时间（EOS）、生长周期（LOS）等物候参数接近站点数据,AG法和D-L法保持NDVI时序曲线整体变化特征的能力较强,提取的SOS和EOS更接近站点数据;（2）人类活动扰动识别应用场景中,S-G法在滤波时能够最大限度地保留时序曲线细节变化,恢复速率相关系数达到0.618,回归估计标准差低于AG法和D-L法,因此识别精度最优。