提升汇流环湿热环境适应性方法研究

目的提高汇流环在湿热环境下的适应能力。方法实物解剖,观察汇流环绝缘材料损坏情况、碳粉堆积情况,在不同温度、湿度下测试绝缘材料绝缘度、抗电强度,碳粉堆积和导电情况,比对不同绝缘材料性能,并找出最适合的绝缘材料,比对滚动汇流环、碳刷组件、刷丝组件,找到解决碳粉堆积的方法。结果汇流环受湿热影响会从接缝处和电缆连接处进入湿气,温度、湿度的上升会使得原绝缘材料性能下降,长时间使用汇流环,碳粉会在汇流环内堆积并受到湿热的影响而导电,局部密封汇流环可以减少湿气进入。PPO材料性能优异,可以替换原绝缘材料从而减少湿热的影响,使用刷丝组件替代碳刷可以避免碳粉的产生。结论综合运用局部密封、绝缘材料改进、碳刷组件改进三种措施,可以有效提高汇流环在湿热环境下的适应能力。     

不同区域城市空气O3和PM2.5累积速率时序模型

利用2017—2018年全国7个区域10个典型城市环境空气O₃和PM_2.5浓度数据，统计污染物累积速率，进而采用回归方法拟合污染物浓度及其累积速率的时间序列模型，分析不同区域污染物时序变化特征差异。结果表明：不同区域O₃浓度时序曲线拟合程度总体高于PM_2.5，石家庄O₃拟合程度最高，西安PM_2.5拟合程度最高。以07：00、14：00分别作为O₃、PM_2.5模拟起点是24 h中的最优模型。不同城市夏季O₃小时浓度时序变化曲线均为单峰形态，O₃浓度及累积速率峰值出现时间可能由城市所处经度决定，太原O₃累积最快，西安O₃消解最快。各城市间冬季PM_2.5小时浓度及其累积速率时序变化曲线形态差异较大，沈阳PM_2.5累积和消解均最快。与浓度相比，城市环境空气O₃和PM_2.5累积速率与光照、扩散条件等有更好的时间相关性。     

Interpretation of roadside PM10 monitoring data from Sunderland,United Kingdom

Roadside PM₁₀ has been monitored by Partisol® at three sitesin Sunderland between August 1997 and February 1998. The sites chosen were an inner city kerbside site; a roadside site adjacentto a dual carriageway on the outskirts of Sunderland with an openaspect; and a rural site.The results indicate that there is a seasonal variation in the relationship between the sites in terms of monitored PM₁₀.In the winter there is a poor correlation between the sites whereas in the summer significant correlations are obtained. Of the sites monitored PM₁₀ is consistently highest at the inner city roadside site. During the summer, exceedances of theU.K. 50 g m^-3 standard (DETR, 2000) are associated with conditions suitable for the build-up of photochemical pollutionhowever during the winter period exceedances are recorded duringa variety of weather conditions.At the dual carriageway site PM_2.5 has also been recorded and contributions to measured PM₁₀ are 77% in summer and68% in winter. The results illustrate a number of inconsistencies between this study utilising the Partisol® andothers reporting results where PM₁₀ has been monitored by TEOM®.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Preliminary air pollution monitoring in San Miguel, Buenos Aires

Passive diffusion samplers were employed in San Miguel(Buenos Aires Metropolitan Area) for a preliminary airpollution monitoring. The highest loads were observedin downtown, compared with an urban background site.Total suspended particulate matter (TSPM) varied from0.257 to 0.033 mg cm^-2 month^-1; dust was examinedfor particle nature and size distribution. A similartrend was observed for nitrogen dioxide (NO₂) andTSPM spatial distribution, suggesting that traffic isthe major pollution source. Sulphur dioxide (SO₂)values were low and rather homogeneous. Levels for theinvestigated pollutants are below EPA's guide linevalues. Geographic (flat area, near to Rio de LaPlata) and climatologic factors (rainfalls andvariable wind directions) contribute to disperse pollutants.     

An Assessment on Variation of Sulphur Dioxide and Particulate Matter in Erzurum (Turkey)

Sulphur dioxide and PM₁₀ levels are investigated in Erzurum during the periods of 1990–2000 heating season to assess air pollution level. For that reason, emissions of sulphur dioxide and particulate matter were calculated by using consumption of fuels and Turkish emission factors. These emission values were evaluated together with air pollution levels, which were measured at six stations in Erzurum atmosphere during 1990–2000 winter periods. Results reveal that in 1990–1994 heating period, there is an increasing trend in the emissions and air pollution levels over Erzurum, and the air quality limits were not met. The daily 24 h limit (short-term limit) was exceeded 127 days in 1992–1993 winter period. The reason for this increase was found to be the switching to use of low-quality fossil fuels instead of cleaner ones. Results also indicated that there was a considerable decrease in emissions of air pollutants and air pollution levels after 1995. This can be explained by the consumption of more high-quality fossil fuels. The correlation coefficient of SO₂ with PM₁₀ is obtained as r² = 0.85, which is a high value supporting the idea that both pollutants are emitted from the same source.     

Atmospheric particulate pollution of Lanzhou using magnetic measurements

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Carbon Dioxide Balance of Wood Substitution: Comparing Concrete- and Wood-Framed Buildings

In this study a method is suggested to compare the net carbon dioxide (CO₂) emission from the construction of concrete- and wood-framed buildings. The method is then applied to two buildings in Sweden and Finland constructed with wood frames, compared with functionally equivalent buildings constructed with concrete frames. Carbon accounting includes: emissions due to fossil fuel use in the production of building materials; the replacement of fossil fuels by biomass residues from logging, wood processing, construction and demolition; carbon stock changes in forests and buildings; and cement process reactions. The results show that wood-framed construction requires less energy, and emits less CO₂ to the atmosphere, than concrete-framed construction. The lifecycle emission difference between the wood- and concrete-framed buildings ranges from 30 to 130 kg C per m² of floor area. Hence, a net reduction of CO₂ emission can be obtained by increasing the proportion of wood-based building materials, relative to concrete materials. The benefits would be greatest if the biomass residues resulting from the production of the wood building materials were fully used in energy supply systems. The carbon mitigation efficiency, expressed in terms of biomass used per unit of reduced carbon emission, is considerably better if the wood is used to replace concrete building material than if the wood is used directly as biofuel.     

国内外军工材料环境试验现状及发展趋势

介绍军工材料环境试验对提高装备环境适应性的重要作用。从不同的技术方面,分析了国内外军工材料环境试验的现状、发展趋势以及主要差距。从规划的制定、新技术新方法的研发以及信息共享方面,提出设想。提出了目前需要研发新的环境试验、评价、管理方法和需要突破的关键技术。     

温泉宾馆室内PM_(10),PM_(2.5),CO_2和~(222)Rn的研究

对广东省 4座温泉宾馆室内外氡(222Rn)浓度和温泉水氡浓度进行研究,同时利用便携式探测器对室内外 PM10,PM2.5,CO2和CO 等污染物暴露水平进行直接测定.结果表明,温泉宾馆室内使用温泉水时氡浓度明显高于广东省室内平均氡浓度.除 CO 外,室内 PM10,PM2.5 和CO2 浓度都较高,其中 PM10 和 CO2 的超标率分别达到 67%和 89%.说明温泉宾馆室内不仅存在一般性污染物,而且存在高浓度的 Rn. 222