TraK装置测定废水中的BOD_5

在对废水中的BOD5进行常规分析时,采用化学稀释法操作繁琐,对稀释倍数估计易发生错误。而利用TraK装置测试样品时,无须进行稀释和化学分析。用该装置对标准样品BOD5的测定结果表明:准确度相对误差为-3.3%～4.3%,精密度的相对误差为-3.5%～5.6%。该仪器测试性能可靠,数据准确度、精密度合格。与化学法对照分析表明,相对误差都在容许范围内,即在可接受范围内。     

基于模糊模式识别的模糊综合评价在高层建筑火灾危险评价中的应用

针对高层建筑火灾危险的特点,建立了高层建筑火灾危险评价的指标体系,并应用层次分析法确定了其权重。根据高层建筑火灾危险评价系统具有多因素、多层次的特点,采用模糊综合评价方法;针对模糊综合评价的不足之处,提出把权广义距离之和最小模糊模式识别运用到模糊综合评价当中,建立了基于模糊模式识别的模糊综合评价模型;该评价模型避免了单因素矩阵的确定和模糊算子的选择问题,用安全状态特征值来表征最终的评价结果,能使评价结果更加准确,可操作性强。通过对陕西某高层建筑火灾危险评价实例证明,该模型具有较好的应用价值,为日常的安全管理和性能化防火设计提供了有用依据。     

基于面积统计的震后烈度评估

选取了较为典型的历史震例,并将这些震例的等震线图数字化.利用这些等震线图数据,直接统计出地震参数和震后不同烈度面积之间的关系,并将该关系和烈度衰减几何模型结合起来,反演震后烈度的具体分布形状,以进行震后烈度分布的预测.     

Sustainability of Current Agricultural Practices in The Cameron Highlands, Malaysia

Cameron Highlands is a mountainous region with steep slopes. Gradients exceeding 20^∘ are common. The climate is favourable to the cultivation of tea, sub-tropical vegetables and flowers (under rain-shelter). Crop production is sustained by high fertiliser and manure applications. However, agriculture in this environment is characterised by high levels of soil erosion and environmental pollution. A study on the sustainability of these agro-ecosystems was conducted. Results indicated that soil loss was in the range of 24–42 ton/ha/yr under vegetables and 1.3 ton under rain-shelter. Sediment load in the vegetable sub-catchment reached 3.5 g/L, 50 times higher than that associated with flowers under rain-shelter and tea. The sediments contained high nutrient loads of up to 470 kg N/ha/yr. The N, P and K lost in runoff from cabbage farms was 154 kg/season/ha, whereas in chrysanthemum farms it was 5 kg. In cabbage farms, the N, P, and K lost through leaching was 193 kg/season/ha. The NO₃–N concentration in the runoff from the cabbage farms reached 25 ppm but less than 10 ppm in runoff from rain-shelters. Inorganic pollution in the rivers was within the acceptable limit of 10 ppm. The sustainability of the agro-ecosystems is in the order of tea { > } rain–shelter ≫ vegetables.     

污染物排放相关指标计算方法的研究

针对传统的污染排放数据指标计算方法存在的问题,提出污染物排放指标应根据排污强度和经济指标确定的新思路,同时提出污染物排放指标数据的快速测算模型设计.建议通过环境监测数据或物料衡算数据确定每个排污单位的平均排污强度,作为计算机处理的参数,再由该排污单位申报每月的经济指标(产量或产值),输入计算机计算其产污量、排污量和去除量.实施计算机管理的关键是选取适当的数据计算模型.新思路应该能够规范计算程序,建立污染源动态数据库,对排污数据实行有效的统计分析.     

北京市某高层建筑高空电磁辐射环境影响分析

选取北京市某代表性高层居民楼顶平台作为高空电磁辐射环境水平监测点进行综合场强和选频监测，评价总体电磁辐射环境水平，并分析监测区域电磁辐射能量的来源。结果表明：该高空监测区域的电磁辐射环境总体水平低于国家规定的公众照射导出限值，但高于地面水平。监测区域主要受30 km 外的中波台影响，其次是9 km 外的中央电视塔。影响最大的是639 kHz频率的中波信号，占100 kHz～300 MHz总场强的95％以上，其次是1．28 MHz频率的中波信号。提出，开展敏感建筑物规划建设时，应考虑中波的传播特性和对环境的影响。     

中国碳排放强度的时空演进及跃迁机制

面对气候变化所带来的生存危机以及环境治理的复杂状况,对中国碳排放强度时空演进的动态监测与预警治理的研究是实现碳排放强度下降目标的关键。文章测算1997—2015年中国大陆30个省区碳排放强度的空间面板数据,采用探索性时空数据分析(ESTDA)方法对中国碳排放强度的空间相关性、集聚特征及其时空跃迁进行空间统计分析,借助分位数回归与时空跃迁嵌套模型,揭示在时间和空间推移的双重作用下中国各省区碳排放强度的时空跃迁机制。研究结果表明:(1)中国30个省区的碳排放强度在时空分布上并不是完全随机状态,各个省区碳排放强度之间具有显著的空间相关性特征,碳排放强度的变动趋势会受到其相临近省区碳排放强度的影响,省域间的碳排放强度在空间分布上呈现"集聚"与"分异"并存的时空演进特征。(2)中国碳排放强度空间集聚趋势增强,具有高度的凝固性和较低的流动性,10个高碳排放强度省区碳排放强度的稳定性将成为制约中国碳排放强度整体跃迁的重点省区,相关省区的跃迁性将成为驱动中国碳排放强度整体跃迁的关键省区。(3)各省区的碳排放强度空间集聚过程中存在时空跃迁的驱动模式和制约模式,分位数回归模型能够很好地解释各驱动因素对碳排放强度时空跃迁的驱动机制,不同响应阶段的驱动因素的分位数与碳排放强度时空跃迁类型之间具有很强的嵌套性。(4)根据各省区碳排放强度时空演进及其跃迁机制的分析结果,进一步提出加强对关键省区碳排放强度的有效监测与治理,加大碳排放的约束力度等差异化的碳减排调控措施。     

Effectiveness of Africa's tropical protected areas for maintaining forest cover

The effectiveness of parks for forest conservation is widely debated in Africa, where increasing human pressure, insufficient funding, and lack of management capacity frequently place significant demands on forests. Tropical forests house a substantial portion of the world's remaining biodiversity and are heavily affected by anthropogenic activity. We analyzed park effectiveness at the individual (224 parks) and national (23 countries) level across Africa by comparing the extent of forest loss (as a proxy for deforestation) inside parks to matched unprotected control sites. Although significant geographical variation existed among parks, the majority of African parks had significantly less forest loss within their boundaries (e.g., Mahale Park had 34 times less forest loss within its boundary) than control sites. Accessibility was a significant driver of forest loss. Relatively inaccessible areas had a higher probability (odds ratio >1, p < 0.001) of forest loss but only in ineffective parks, and relatively accessible areas had a higher probability of forest loss but only in effective parks. Smaller parks less effectively prevented forest loss inside park boundaries than larger parks (T = ?2.32, p < 0.05), and older parks less effectively prevented forest loss inside park boundaries than younger parks (F_2,154 = ?4.11, p < 0.001). Our analyses, the first individual and national assessment of park effectiveness across Africa, demonstrated the complexity of factors (such as geographical variation, accessibility, and park size and age) influencing the ability of a park to curb forest loss within its boundaries.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

近52年来洞庭湖流域气象干旱的时空分布特征

基于洞庭湖流域84个气象站点1962~2013年的逐日气象资料,利用综合干旱指数(CI)对洞庭湖流域气象干旱的时间和空间特征进行分析。结果表明:在过去52 a,区域性干旱强度较强的时段以夏季、秋季、夏秋和秋冬时节为主;区域干旱强度在春季、夏季、夏秋、冬季呈上升趋势;秋冬时节和年干旱强度变化不明显;春夏时节、夏秋时节、秋冬时节和冬春时节的平均干旱强度比春、夏、秋、冬单个季节的平均干旱强度大。小波分析表明,区域干旱强度的周期以10a为主周期,5 a和22 a为次周期。近52 a来,历年干旱站次比主要集中于10%~30%之间,多表现为区域性干旱,以夏季和秋季的干旱范围较大;干旱频率高发时期主要为夏季、夏秋时节和秋季。干旱频率高发地主要以流域的南部山地和北部的洞庭湖平原为主,西北部的山地发生干旱相对较少,衡邵盆地随季节变化干旱频率易发生高低值转换。