蜂窝流道热沉强化传热数值模拟

热沉是模拟太空深冷环境的核心部件。为提高空间深冷环境的模拟效果,更好地满足型号试验需求,设计了一种蜂窝流道热沉。利用流体力学理论和有限元方法对蜂窝热沉内部流体的流动和强化传热进行数值模拟,分析流道结构参数对流体流动和换热的影响,确定最优的流道结构参数。结果表明,同等条件下蜂窝热沉表面温度低于管板式热沉5 K左右,温度均匀性可达到±2 K;流道深度和间距是影响流体在热沉中流动与传热的重要因素,合理选择流道结构参数可以提高热沉的换热性能;需要综合考虑传热和阻力问题来确定最优的流道结构参数,最优的蜂窝热沉流道间距为75 mm,深度为10 mm。     

实时尾气检测系统OEM的应用

机动车尾气排放实时检测系统OEM是基于车辆实际行驶路况的新型车载尾气检测系统。该系统突破了传统的定点尾气收集数据的局限性，能够方便快捷地获得不同路段、不同车型、不同时段的以秒为单位的尾气排放数据以及包括速度和加速度在内的瞬间车辆行驶数据。文中对OEM系统的基本原理和方法进行了简单的介绍，并给出了应用该系统在北京市交通网络测试尾气的一些初始结果。     

某草浆造纸企业污染物综合利用措施研究

国内以草浆为原料制浆造纸的各类企业占造纸企业总数的65%以上。分析以某草浆为主的造纸企业生产过程中产生污染物的种类及特点;并根据其不同特征,有针对性地提出了节约生产用水、循环利用处理水、提高黑液提取率及碱回收车间废水零排放的方法;同时探讨了造纸企业排放的废渣、废气及污泥等资源综合利用措施。该造纸企业通过几年来的努力,在节水减污方面取得了一定的实效。为同行业处理污染物,综合和循环利用资源提供了参考。     

Research on ecosystem services of water conservation and soil retention: a bibliometric analysis

Environmental Science and Pollution Research - Water conservation and soil retention are two essential regulating services that are closely related, and their relationship might produce synergies...     

Effects of productivity on biodiversity in forest ecosystems across the United States and China

In the global campaign against biodiversity loss in forest ecosystems, land managers need to know the status of forest biodiversity, but practical guidelines for conserving biodiversity in forest management are lacking. A major obstacle is the incomplete understanding of the relationship between site primary productivity and plant diversity, due to insufficient ecosystem‐wide data, especially for taxonomically and structurally diverse forest ecosystems. We investigated the effects of site productivity (the site's inherent capacity to grow timber) on tree species richness across 19 types of forest ecosystems in North America and China through 3 ground‐sourced forest inventory data sets (U.S. Forest Inventory and Analysis, Cooperative Alaska Forest Inventory, and Chinese Forest Management Planning Inventory). All forest types conformed to a consistent and highly significant (P < 0.001) hump‐shaped unimodal relationship, of which the generalized coefficients of determination averaged 20.5% over all the forest types. That is, tree species richness first increased as productivity increased at a progressively slower rate, and, after reaching a maximum, richness started to decline. Our consistent findings suggest that forests of high productivity would sustain few species because they consist mostly of flat homogeneous areas lacking an environmental gradient along which a diversity of species with different habitats can coexist. The consistency of the productivity–biodiversity relationship among the 3 data sets we examined makes it possible to quantify the expected tree species richness that a forest stand is capable of sustaining, and a comparison between the actual species richness and the sustainable values can be useful in prioritizing conservation efforts.     

Applicability of hybrid bionic optimization models with kernel-based extreme learning machine algorithm for predicting daily reference evapotranspiration: a case study in arid and semiarid regions,China

Environmental Science and Pollution Research - The accurate prediction of daily reference crop evapotranspiration (ETO) enables effective management decision-making for agricultural water...     

Research status,challenges and future prospects of renewable synthetic fuel catalysts for CO2 photocatalytic reduction conversion

Environmental Science and Pollution Research - In recent years, with global climate change, the utilization of carbon dioxide as a resource has become an important goal of human society to achieve...     

Multi-dimensional influence measurement of urbanization on the quality of natural living environment in China

Environment, Development and Sustainability - With the rapid development of industrialization and urbanization and the continuous improvement of social productivity, people are increasingly...     

Study on the relationship between the incidence of influenza and climate indicators and the prediction of influenza incidence

In recent 2 years, the incidence of influenza showed a slight upward trend in Guangxi; therefore, some joint actions should be done to help preventing and controlling this disease. The factors analysis of affecting influenza and early prediction of influenza incidence may help policy-making so as to take effective measures to prevent and control influenza. In this study, we used the cross correlation function (CCF) to analyze the effect of climate indicators on influenza incidence, ARIMA and ARIMAX (autoregressive integrated moving average model with exogenous input variables) model methods to do predictive analysis of influenza incidence. The results of CCF analysis showed that climate indicators (PM2.5, PM10, SO₂, CO, NO2, O₃, average temperature, maximum temperature, minimum temperature, average relative humidity, and sunshine duration) had significant effects on the incidence of influenza. People need to take good precautions in the days of severe air pollution and keep warm in cold weather to prevent influenza. We found that the ARIMAX (1,0,1)(0,0,1)₁₂ with NO₂ model has good predictive performance, which can be used to predict the influenza incidence in Guangxi, and the predicted incidence may be useful in developing early warning systems and providing important evidence for influenza control policy-making and public health intervention.