“十一五”乌鲁木齐市PM10浓度变化趋势及影响因素分析

对“十一五”乌鲁木齐市PM10浓度变化趋势及影响因素分析,结果表明污染治理措施成效显著,年均浓度和栗暖期浓度值呈下降趋势。但由于综合治理措施不到位,非采暖期浓度值呈上升趋势。     

施肥类型和水热变化对农田土壤氮素矿化及可溶性有机氮动态变化的影响

为了揭示土壤水分、温度和添加不同氮肥对大沽河流域农田土壤氮素矿化的影响,设置对照(CK)、添加尿素N 120mg·kg~(-1)(Ur)和添加尿素N 36 mg·kg~(-1)+有机肥(相当于添加N 120 mg·kg~(-1),UM)这3个处理进行为期84 d的室内恒温培养实验,实验共设3个培养温度(15、25和35℃)和3个水分梯度[60%、75%和90%田间持水量(WHC)].结果表明,施肥类型和培养温度对土壤氮素矿化速率、累积矿化量和氮潜在矿化势(N0)均具有显著影响(P0.01).与CK处理相比,Ur和UM处理的矿化速率和累积矿化量分别增加了1.46~8.17和2.00~8.15倍.各施肥处理的土壤氮矿化速率和累积矿化氮量随温度升高而增加,且各温度梯度之间差异均达到显著水平(P0.05).与未施肥处理相比,Ur和UM施肥处理均能够显著提高土壤中可溶性有机氮(SON)的含量,且施肥处理土壤中SON含量与氮素累积矿化量之间有显著负相关关系,表明SON作为一个不可忽视的组分,参与了土壤氮素矿化过程.升高温度能显著提高土壤中SON的矿化速率和矿化强度,但水分对各处理土壤的SON无显著影响.此外,施肥处理显著降低了土壤氮矿化的温度敏感性(Q10)(P0.05),尿素配施有机肥处理的土壤的氮矿化温度敏感系数最低(Q10=1.01),说明配施有机肥显著降低了土壤氮素矿化速率对温度变化响应的强度,这有利于减缓高温条件下矿质氮的释放速率,并提升作物对氮素的利用效率.     

重量法测定空气中PM10的不确定度评定研究

根据重量法测定空气中PM10的测量方法原理,建立数学模型,从样品现场采样与实验室测试相结合引入各不确定度分量,分析并评定用重量法测定空气中PM10的不确定度,确定合成不确定和扩展不确定度.从各不确定度分量大小,最终确定测量不确定度影响因素并加以有效控制及改进,改善测量方法和手段,从而为空气中PM10浓度测定提高检测数据准确性,提供科学检测依据.     

环境应急网络视频监控系统设计

文章分析了当前我国环境应急监测的现状,阐述了在环境应急监测中加强信息技术应用的重要性和必要性,介绍了视频监控技术的发展演变过程以及网络视频监控技术在环境应急监测中的优势,提出了基于3G网络视频监控技术的环境应急监测系统,主要由前端视频采集、3G传输网络、指挥中心、监控客户端等四部分组成,可以将事故现场的视频监控信号快速发送至各级指挥中心,提高应急处置效率。     

长沙市城区典型交通路口PM_(10)和PM_(2.5)污染特征研究

利用车载环境空气质量监测系统对长沙市城区典型交通路口的近地面空气质量进行了实时监测。结果表明,在监测时段(14∶00~20∶00)内,该监测点环境空气中PM10的小时质量浓度范围在0.097~0.222mg/m3之间,平均值0.163mg/m3;PM2.5的小时质量浓度范围在0.050~0.158mg/m3之间,平均值0.103mg/m3。PM2.5/PM10比值在48.1%~76.6%之间,平均值62.4%。PM10与PM2.5质量浓度在星期一相对较低,星期二有所升高,星期三至周末总体上保持基本稳定。在监测时段PM10与PM2.5小时质量浓度呈现先降后升的变化规律,即14∶00~15∶00,PM10与PM2.5质量浓度相对较高,16∶00左右降至最低,从17∶00开始逐渐升高,20∶00达到峰值。PM10和PM2.5的质量浓度变化与车流量和车速密切相关,温度、相对湿度和风速等气象因素对PM10和PM2.5质量浓度的变化影响也较显著。     

可持续发展战略与上海“十五”计划编制的研究

“十五”计划是上海市进入21世纪的第1个5年计划,从提升自身发展质量和国际综合竞争能力的要求分析了将可持续发展战略纳入上海“十五”计划编制工作的必要性和重要性,围绕思想创新、目标创新、框架创新、指标创新等4个方面探讨了以可持续发展为定位的上海“十五”计划编制思路。     

曲面效应法优化辅酶Q10发酵条件

以根癌土壤杆菌(Agrobacterium tum efaciens)1.1416的突变株AGR 0610为出发菌株,采用P lackett-Burm an设计法(P lackett-Burm an design,P-B)对影响AGR 0610发酵产辅酶Q10的相关因素进行了研究,选取到4种有显著效应的因素:糖蜜、大豆蛋白胨、玉米浆和蛋氨酸.再采用响应曲面法(response surface m ethodology,RSM)对这4种因素的最佳水平范围进一步探讨,得到二次回归方程,优化了培养基组成.当这4种因素分别取值为1.02%、0.49%、0.29%和0.34%时,辅酶Q10产量有最大预测值38.88 mg/L,并被实验所证实.图6表4参8     

Formation of secondary inorganic aerosols by power plant emissions exhausted through cooling towers in Saxony

Background, aim, and scope  The fraction of ambient PM₁₀ that is due to the formation of secondary inorganic particulate sulfate and nitrate from the emissions of two large, brown-coal-fired power stations in Saxony (East Germany) is examined. The power stations are equipped with natural-draft cooling towers. The flue gases are directly piped into the cooling towers, thereby receiving an additionally intensified uplift. The exhausted gas-steam mixture contains the gases CO, CO₂, NO, NO₂, and SO₂, the directly emitted primary particles, and additionally, an excess of ‘free’ sulfate ions in water solution, which, after the desulfurization steps, remain non-neutralized by cations. The precursor gases NO₂ and SO₂ are capable of forming nitric and sulfuric acid by several pathways. The acids can be neutralized by ammonia and generate secondary particulate matter by heterogeneous condensation on preexisting particles. Materials and methods  The simulations are performed by a nested and multi-scale application of the online-coupled model system LM-MUSCAT. The Local Model (LM; recently renamed as COSMO) of the German Weather Service performs the meteorological processes, while the Multi-scale Atmospheric Transport Model (MUSCAT) includes the transport, the gas phase chemistry, as well as the aerosol chemistry (thermodynamic ammonium–sulfate–nitrate–water system). The highest horizontal resolution in the inner region of Saxony is 0.7 km. One summer and one winter episode, each realizing 5 weeks of the year 2002, are simulated twice, with the cooling tower emissions switched on and off, respectively. This procedure serves to identify the direct and indirect influences of the single plumes on the formation and distribution of the secondary inorganic aerosols. Results and conclusions  Surface traces of the individual tower plumes can be located and distinguished, especially in the well-mixed boundary layer in daytime. At night, the plumes are decoupled from the surface. In no case does the resulting contribution of the cooling tower emissions to PM₁₀ significantly exceed 15 μgm⁻³ at the surface. These extreme values are obtained in narrow plumes on intensive summer conditions, whereas different situations with lower turbulence (night, winter) remain below this value. About 90% of the PM₁₀ concentrations in the plumes are secondarily formed sulfate, mainly ammonium sulfate, and about 10% originate from the primarily emitted particles. Under the assumptions made, ammonium nitrate plays a rather marginal role. Recommendations and perspectives  The analyzed results depend on the specific emission data of power plants with flue gas emissions piped through the cooling towers. The emitted fraction of ‘free’ sulfate ions remaining in excess after the desulfurization steps plays an important role at the formation of secondary aerosols and therefore has to be measured carefully.     

北京市2005年夏季大气颗粒物污染特征及影响因素

对2005年7～8月北京市不同功能区8个采样点PM10和PM2.5的浓度水平、空间分布、PM10/PM2.5比值进行了分析,并讨论了PM10和PM2.5的日变化特征及影响因素.结果表明,北京市夏季PM10和PM2.5日均浓度为155.37 μg/m3和87.70 μg/m3,分别为国家二级标准和美国PM2.5标准的1.04倍和1.35倍;PM2.5、PM10浓度在不同功能区存在一定差异;PM2.5和PM10的日变化以白天高,夜间低为主,且不同功能区的最高值对应于城市居民活动的不同高峰期;在湿度较高的情况下,PM2.5、PM10与湿度呈一定正相关性,且湿度对PM2.5的影响更大;降水前后PM2.5、PM10浓度变化情况表明降水的主要作用是清除粗粒子,对PM2.5的影响则较小.     

传统手工法和自动监测法检测空气中颗粒物的对比

分别运用传统的中流量颗粒物采样器和RP1400 a自动测尘仪,对空气中颗粒物（TSP和PM10）进行同步采样检测,结果表明,两种方法的检测结果存在着明显的系统偏差,前者的检测结果较后者偏高。