洪涝灾害条件下疏散交通生成预测方法

为有助于有关部门更准确预测洪涝灾害受灾民众的疏散量,结合非集计数据和集计数据的优点,提出分区集计数据的概念,设计了受灾区域分区方法,并通过意向偏好(SP)调查法对我国居民在洪涝条件下疏散交通需求数据进行调查。在此基础上,引入BP神经网络建立基于分区集计数据的疏散交通生成预测模型。利用调查数据进行实证分析发现,所设计方法取得了较好的预测效果,鲁棒性较好,平均相对预测误差仅为1.8%,其预测效果明显优于现有的非集计和整集计模型。     

基于开发需求的安徽沿江地区生态经济分区

从压力、状态和人类响应3个方面,构建了生态经济分区指标体系,结合经济开发需求的评价结果,以县(市、城区)为基本评价单元,利用主成分分析与系统聚类的方法,根据自上而下的专家定性评估,遵循空间邻近性原则,将安徽沿江地区划分为7个生态经济类型,即:合肥污染防治与城镇生态优化区、巢滁湖泊湿地保护与平原生态农业区、马芜铜宣工业污染防治与城镇生态优化区、宣南生态农业与水土保持区、安庆平原农业与湿地生态保护区、池州森林保育与生态农业区以及皖西水源保护与森林保育区.     

陕西省水资源供求指数和综合干旱指数及其时空分布

识别区域的干旱时空特征对于防旱抗旱具有重要指导意义。论文采用两种方法研究了陕西省干旱时空分布特征并比较了两种方法在应用中的优缺点：其一,考虑社会经济因素对干旱的影响,采用基于水资源供水和需水平衡的陕西省社会经济干旱指标（水资源供求指数）;其二,结合SPI、PDSI和SPEI的特点,运用模糊综合法建立了综合干旱指数。结果表明：陕西省干旱发生频率很高,南北多发生轻微干旱,中部多发生中重度干旱。陕西省干旱在空间上分布差异大,两种方法均表明咸阳、西安、渭南和铜川地区旱情最为严重。在水资源量存在巨大差异的地区,如商洛与榆林,仅用一种类型的干旱指标无法全面体现实际情况,两种方法的结论存在差异：综合干旱指数表明榆林干旱较重,但供求指数为轻旱;商洛供水可满足需水,但综合干旱指数为轻旱。气象干旱指数,在水资源短缺的地区或自然生态系统中,结果更贴近于实际;社会经济干旱指数——水资源供求指数,更适宜用于水资源极其丰富且供水能力强的地区。     

基于UML的放射源贮存库管理系统设计

随着放射性同位素在油井钻探、测试等领域中的广泛应用,放射源的种类及数量越来越大,使用频率越来越高,传统的管理方法已经不适应现代条件下的放射源管理需求。本文从放射源管理中的重要环节——贮存库管理系统入手,以UML为工具,对贮存库管理系统的需求模型和系统模型进行了设计,以提高放射源管理水平。     

提高快速法测定C OD准确度及精密度的方法

介绍了用快速法测定COD分析中提高准确度及精密度的方法。     

对氯气校正法测定高氯废水化学需氧量的方法研究

氯气校正法(HJ/T70-2001)是测定高氯废水化学需氧量的国标方法,为了减少样品测定过程带来的环境污染,研究在不改变HJ/T70-2001氧化体系及测试条件的情况下,将取样体积由20 mL减半为10 mL,试剂的使用量相应减半,对方法的检出限、相对误差、相对标准偏差等指标进行验证。结果表明,该方法的检出限符合要求,准确度较高,精密度较好,可用于高氯废水化学需氧量的测定。     

The dynamic changes of arsenic biotransformation and bioaccumulation in muscle of freshwater food fish crucian carp during chronic dietborne exposure

Dietary uptake is the major way that inorganic arsenic (iAs) enters into benthic fish; however, the metabolic process of dietborne iAs in fish muscle following chronic exposure remains unclear. This was a 40-day study on chronic dietborne iAs [arsenite (AsIII) and arsenate (AsV)] exposure in the benthic freshwater food fish, the crucian carp (Carassius auratus), which determined the temporal profiles of iAs metabolism and toxicokinetics during exposure. We found that an adaptive response occurred in the fish body after iAs dietary exposure, which was associated with decreased As accumulation and increased As transformation into a non-toxic As form (arsenobetaine). The bioavailability of dietary AsIII was lower than that of AsV, probably because AsIII has a lower ability to pass through fish tissues. Dietary AsV exhibited a high potential for transformation into AsIII species, which then accumulated in fish muscle. The largely produced AsIII considered more toxic at the earlier stage of AsV exposure should attract sufficient attention to human exposure assessment. Therefore, the pristine As species and exposure duration had significant effects on As bioaccumulation and biotransformation in fish. The behavior determined for dietborne arsenic in food fish is crucial for not only arsenic ecotoxicology but also food safety.     

The influence of Chinese population policy change on resources and the environment

Universal two-child policy has been implemented since the end of 2015 in China. This policy is anticipated to bring a significant increase in the total population, with profound influences on the resources and environment in the future. This paper analyzes the changing dynamics of urban and rural population, and forecasts urban and rural population from 2016 to 2030 at national and provincial scale using a double log linear regression model. Drawing upon the results of these two predictions, the impact of the population policy change on Chinese resources consumption and environmental pollution are predicted quantitatively. Given the future total population maintains current levels on resources consumption and environmental emission, the additional demand of resources and environment demand for the new population is forecasted and compared against the capacity on supply side. The findings are as follows: after implementing the universal two-child policy, China’s grain, energy consumption, domestic water demand, and pollutant emissions are projected to increase at different rates across provinces. To meet the needs arising from future population growth, food and energy self-sufficiency rate will be significantly reduced in the future, while relying more on imports. Stability of the water supply needs to be improved, especially in Beijing, Henan, Jiangsu, Qinghai, and Sichuan where the gap in future domestic water demand is comparatively larger. Environmental protection and associated governing capability are in urgent need of upgrade not least due to the increasing pressure of pollution.     

Assessing the long-term supply risks for mineral raw materials—a combined evaluation of past and future trends

This paper develops a method for identifying and assessing long-term supply risks for mineral raw materials. The method is based on a combined evaluation of past and future supply and demand trends. By analysing raw material boom and bust cycles over the past 50 years, we have quantified indicators and defined benchmarks for identifying critical market situations. By applying the method, risks for supply shortage may be identified at an early stage. In addition, a numerical evaluation model has been developed for better comparison between various mineral raw materials. Compared to other assessment methods this method uses specific benchmarks for each raw material to better assess supply risks. The method is embedded within a systematic and comprehensive analytical approach.     

Forecasting China’s primary energy demand based on an improved AI model

An improved energy demand forecasting model is built based on the autoregressive distributed lag (ARDL) bounds testing approach and an adaptive genetic algorithm (AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization, and technological progress as the input variables. On the basis of historical annual data from 1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively.