城市交通大气与土壤重金属对小蜡生物富集作用的影响

选择合肥市区交通干道、城郊公路和森林公园作为具有不同交通流量的路段,通过火焰原子吸收法,测定土壤和小蜡叶片中的w(Cu),w(Zn),w(Pb),w(Cd)和w(Cr);运用统计方法研究土壤和小蜡叶片中重金属含量的差异和相关性,以及与城市交通大气污染的关系.结果表明:市区交通干线和城郊公路的土壤中w(Cu),w(Zn),w(Pb),w(Cd)和w(Cr)均高于对照点(森林公园),且市区交通干线与对照点的土壤中重金属含量差异显著;小蜡叶片对5种重金属富集量与土壤中的相应重金属含量没有明显相关性,这表明叶片富集的重金属主要来源于道路交通产生的大气重金属污染物,而非主要从土壤中吸收获得;小蜡叶片对大气中的Pb和Cr的富集能力较强,其生物浓缩系数分别为5.50和3.43,说明小蜡可能是Pb和Cr的良好指示植物,可用于环境监测.     

Impacts of Upstream Building Width and Upwind Building Arrangements on Airflow and Pollutant Dispersion in a Street Canyon

A two-dimensional numerical model for evaluating the wind flow and pollutant dispersion within a street canyon was first developed using the FLUENT code, which was then validated against a wind tunnel experiment. Then, the effects of the upstream building width and upwind building arrangement on the airflow and pollutant dispersion inside an isolated street canyon were investigated numerically. The numerical results revealed that: (1) the in-canyon vortex center shifts downwards as the upstream building width increases; (2) the recirculation zone covers the entire upstream building roof for the cases when W/H = 0.5, 1.0, 1.5, and 2.0 (W is the upstream building width and H is the building height), whereas the flow reattaches the upstream building roof for the cases when W/H = 2.5 and 3.0; (3) when the upstream building width is shorter than the critical width W_C (= 2H), an increase in the upstream building width leads to an increase in the pollution level on the leeward wall of the canyon and a decrease in the roof-level concentrations at the upstream building; (4) when the upstream building width is longer than the critical width, the roof-level concentrations at the upstream building are negligibly small and the pollution level on the leeward wall of the canyon is almost unaffected by a further increase in the upstream building width; (5) when the buildings are placed upwind of the canyon, the flow attaches the upstream building roof and, therefore, almost none of the pollutants are distributed on the upstream building roof; and (6) the pollution levels inside the canyon and on the downstream building roof increase significantly with the number of upwind buildings.     

城市大气环境治理成本核算及其总量、结构分析——以西安市为例

基于单位成本分析模型对2000—2009年西安市大气环境治理的价值量进行了系统核算,并从总量与结构两方面对核算结果进行了深入和全面的分析。结果表明,从西安市历年大气环境的实际治理成本(除2002、2006、2009年)来看,该市在大气环境治理方面的投资基本上逐年增加,但是增加幅度较小,而大气环境虚拟治理成本在一般年份(除2002、2006、2009年)总体上呈现先增加后减小的变化趋势。可见,西安市为改变环境污染状况,不断增加大气环境治理方面的投资,但在初期治理资金缺口仍在增加,而随着投资的持续增加,许多大气环境治理设施的建立与作用的发挥,大气环境污染状况逐渐减轻,治理资金缺口开始变小;在核算年份中,西安市工业大气环境污染治理的重点主要放在了烟尘方面,城镇生活SO2虚拟治理成本在生活废气总虚拟治理成本中所占比例最高。最后,针对发现问题,对该市今后大气环境治理工作的方向和措施给出了建议。     

广州白云国际机场飞机大气污染物排放分析

根据收集到的2008-2012年广州白云国际机场航班起降次数，参考《珠江三角洲非道路移动源排放清单开发》飞机污染物估算方法及排放因子，计算出此期间机场飞机大气污染物排放量，并与2010-2012年广州市机动车污染物排放情况对比。结果表明：飞机大气污染物排放量随客运量的增长呈逐年上升趋势，而与机动车排放相比，飞机大气污染物排放量较小，故现阶段仍应以机动车作为移动源污染控制的重点。     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

Military humanitarian and disaster governance networks in Southeast Asia: framework and analysis

Behind humanitarian assistance and disaster relief (HADR) efforts are governance networks of actors working together to facilitate, coordinate, and deliver joint aid and response initiatives. Militaries are key stakeholders in these networks because of their unique capabilities, particularly in Southeast Asia. This paper explores the role of military governance networks in shaping HADR affairs. It presents a framework for examining military-to-military relational structures in humanitarian and disaster contexts using network theory and social network analysis. It also assesses the nature of military ties and their influence on two capability areas essential to humanitarian activities in the region: (i) the distribution of military assets and equipment used in HADR; and (ii) the coordination of HADR exercises and training. This paper seeks to provide insights into how governance network features and properties affect the capacity of ASEAN (Association of Southeast Asian Nations) militaries to use available resources efficiently and to achieve shared objectives in regional disaster response.     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

大数据解析技术在大气环境监测中的应用研究

针对近年来新兴的大数据及挖掘、分析技术,对大数据解析技术在环境科学研究中的应用进行了分析和探析。以城市局部地区大气细颗粒污染物PM2.5浓度计算为例,筛选了PM2.5浓度历史数据、气象条件、交通状况、人群活动情况、网格道路状况等数据为影响特征量,分析了用神经网络法进行大数据解析和推演的原理和数学过程,是用数学、计算机、统计等方法研究解决多元、非线性复杂环境问题的一种新的探索。     

燃煤电厂大气污染物排放考核时间间隔的建议

新的《火电厂大气污染物排放标准》和新《环境保护法》实施后，燃煤火电企业的依法治企自觉性不断提高，但由于不同的环保管理文件对超标处罚依据和处罚手段不同，造成政府对企业处罚的自由裁量权加大，对企业造成一定的压力与困惑。结合企业实际运行情况对燃煤电厂大气污染物排放考核时间间隔提出建议。