氮掺杂二氧化钛负载钒磷氧催化氧化NO的实验研究

以VPO为活性组分,N掺杂TiO 2为载体,采用浸渍法制备了VPO/TiN催化剂,基于单因素实验研究了其对NO的选择性催化氧化(SCO)性能以及抗硫抗水性能。研究表明:当P/V为1/5、N/Ti为1、活性组分负载量为10%、焙烧温度为350℃时,催化剂的SCO活性最好,NO氧化率达到61%;光致发光光谱(PL)表征显示N掺杂TiO 2在催化剂表面形成的氧空位可增强催化剂对O 2的吸附;VPO/TiN催化剂抗硫抗水性能较强,反应后的催化剂表面未发现硫酸根的特征峰,水蒸气主要通过与NO竞争吸附占据活性位点来抑制催化剂的SCO活性。     

2015～2018年太原市臭氧污染特征分析

基于太原市2015年1月~2019年2月的空气质量监测数据,分析了太原市近地面臭氧浓度变化特征。结果表明:2015~2018年太原市臭氧年平均浓度为78.42、82.33、95.87、103.77μg/m 3,臭氧浓度存在加速上升趋势;臭氧浓度逐日变化范围为5~270μg/m 3,共有181 d超过GB 3095—2012《环境空气质量标准》二级标准限值(160μg/m 3),超标时段主要集中于5~8月份;臭氧浓度日变化呈单峰型分布,峰值与谷值时段分别为14∶00~16∶00和6∶00~7∶00;臭氧浓度有明显的月变化规律,峰值与谷值时段分别为6~7月和1月、12月;臭氧浓度还表现出显著的季节变化规律,按浓度高低依次排序为夏季、春季、秋季和冬季;臭氧浓度与NO 2、CO、PM 2.5浓度呈负相关性。     

Regionalization based on spatial and seasonal variation in ground-level ozone concentrations across China

Owing to the vast territory of China and strong regional characteristic of ozone pollution,it's desirable for policy makers to have a targeted and prioritized regulation and ozone pollution control strategy in China based on scientific evidences. It's important to assess its current pollution status as well as spatial and temporal variation patterns across China.Recent advances of national monitoring networks provide an opportunity to insight the actions of ozone pollution. Here, we present rotated empirical orthogonal function(REOF)analysis that was used on studying the spatiotemporal characteristics of daily ozone concentrations. Based on results of REOF analysis in pollution seasons for 3 years' observations, twelve regions with clear patterns were identified in China. The patterns of temporal variation of ozone in each region were separated well and different from each other, reflecting local meteorological, photochemical or pollution features. A rising trend in annual averaged Eight-hour Average Ozone Concentrations(O_3-8 hr) from 2014 to 2016 was observed for all regions, except for the Tibetan Plateau. The mean values of annual and 90 percentile concentrations for all 338 cities were 82.6 ± 14.6 and 133.9 ± 25.8 μg/m~3,respectively, in 2015. The regionalization results of ozone were found to be influenced greatly by terrain features, indicating significant terrain and landform effects on ozone spatial correlations. Among 12 regions, North China Plain, Huanghuai Plain, Central Yangtze River Plain, Pearl River Delta and Sichuan Basin were realized as priority regions for mitigation strategies, due to their higher ozone concentrations and dense population.     

Development of monitoring technology for airborne particulate matter

Particulate matter suspended in the air has adverse effects onhuman health. Its level of concentration is an important parameter in evaluating the degree of hazard it poses to the atmosphere. Conventional methods used in measuring particulatematter are often filter-based, which indicates some disadvantagesbecause such a base requires labor and time. In this study, to achieve real-time measurements, a new electrical method was developed for measuring PM10 and PM2.5 concentrations. The basicprinciple is to electrically charge particles passing through thePM inlet using a corona charger and measure the currents createdby charged particles to obtain the number concentration of particulate matter. A new type inlet based on the particle cupimpactor configuration was designed and its performance was evaluated. A unipolar diffusion charger was developed and thecharger's efficiency was determined experimentally in terms ofPn, which represents the penetration through the charger,P, times the average charge number acquired by a particle,n, for different particle sizes. The correlation was constructed between the PM10 (or the PM2.5) mass concentrationsand the electrical currents due to particles, which were chargedby the diffusion charger.     

龙岩市区大气颗粒物中多环芳烃的种类和时空分布特征及来源

采用恒能量同步荧光法检测了龙岩市大气颗粒物样品中的多环芳烃(PAHs),比较了龙岩市区大气颗粒物中多环芳烃含量的差异以及不同季节对多环芳烃含量的影响,讨论了其分布规律及污染源。     

Pollution prevention at ports: clearing the air

Seaports are major hubs of economic activity and of environmental pollution in coastal urban areas. Due to increasing global trade, transport of goods through ports has been steadily increasing and will likely continue to increase in the future. Evaluating air pollution impacts of ports requires consideration of numerous sources, including marine vessels, trucks, locomotives, and off-road equipment used for moving cargo. The air quality impacts of ports are significant, with particularly large emissions of diesel exhaust, particulate matter, and nitrogen oxides. The health effects of these air pollutants to residents of local communities include asthma, other respiratory diseases, cardiovascular disease, lung cancer, and premature mortality. In children, there are links with asthma, bronchitis, missed school days, and emergency room visits. The significance of these environmental health impacts requires aggressive efforts to mitigate the problem. Approaches to mitigation encompass a range of possibilities from currently available, low-cost approaches, to more significant investments for cleaner air. Examples of the former include restrictions on truck idling and the use of low-sulfur diesel fuel; the latter includes shore-side power for docked ships, and alternative fuels. A precautionary approach to port-related air pollution would encourage local production of goods in order to reduce marine traffic, greener design for new terminals, and state-of-the art approaches to emissions-control that have been successfully demonstrated at ports throughout the world.     

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.     

evaluation of a measurement method for forest vegetation in a large-scale ecological survey

We evaluate a field method for determining species richness andcanopy cover of vascular plants for the Forest Health MonitoringProgram (FHM), an ecological survey of U.S. forests. Measurementsare taken within 12 1-m² quadrats on 1/15 ha plots in FHM.Species richness and cover are determined for four height classes(strata) within each quadrat and aggregated by stratum over the entireplot. We estimated (1) the agreement between experienced trainers andinexperienced technicians who collected the data on this survey(accuracy) and (2) the agreement among the technicians (precision) forresults on species richness and cover from 3 test plots at 3 timeintervals. The methods appear to be highly precise, although somediscrepancies with the values obtained by the trainers were found.Trainers found significantly more species in the ground stratum (0–0.6 m) and measured significantly more cover in the uppermost stratum(>4.9 m). The proportion of variation due to measurement error andtemporal variability was less than 13% for species richness (all strata)and cover (all but one stratum). This indicates that the method issuitable for monitoring changes in species richness and canopy coverfor a large-scale synoptic monitoring project such as FHM.     

太湖水质氮素质量浓度时空差异特征及影响因素分析

通过对2014—2016年湖体水质中氮素质量浓度分析,结合出入湖总氮浓度、水量、湖体水生生态等影响因素,发现太湖水体中总氮浓度呈现逐年下降的趋势,各监测点位总氮为0.530 mg/L～5.51 mg/L,时空分布不均,差异明显。时间上,总氮浓度表现为春季最高,夏季和秋季最低,且月均值变化曲线呈现出规律的正弦函数波形。空间上,总氮浓度大致表现出由西部湖区向东部湖区递减的趋势,呈现西部湖区﹥北部湖区﹥南部湖区﹥湖心区﹥东部湖区。要改善湖体水质,不仅要切断污染源,而且要加强水生生态功能修复。     

大气污染物影响因素的灰色关联分析

运用灰色系统理论，对产生和影响城市大气主要污染物的相关因素，利用灰色关联分析方法进行了量化分析研究，根据研究结果，提出了控制大气污染的防治对策．