离子色谱法测定PM_(2.5)中硫酸根离子含量不确定度评议

准确测定大气颗粒物中水溶性组份对分析污染物来源及身体健康具有重要意义。本文采用离子色谱法测定PM2.5中硫酸根离子含量,并对测定的不确定度进行分析。分析过程不确定度来源是样品重复性测量引入不确定度,样品测量准确性引入不确定度和标准曲线的不确定度。应用不确定度评定理论,计算硫酸根离子的合成不确定度。结果表明,滤膜中硫酸根离子本底浓度高低与剪裁滤膜环节是不确定度的主要来源。为了提高分析的准确性,建议使用本底低的滤膜,并取整张滤膜进行分析。     

宝钢厂区植被碳储量及其固碳效益评价

以著名钢铁企业上海宝钢为例,基于厂区植被调查、航片数字化解释、优势种生物量测定及模型建立,对宝钢厂区植被碳储量和固碳能力进行估算,并通过碳税法对其固碳效益进行评价,以期为城市工业区绿地群落配置和绿化树种选择、企业绿化建设的费用效益分析提供更为科学的依据。结果表明:宝钢厂区植被总碳储量为3992.99～4736.17 t,固碳效益为13507.33～16185.85万元;平均碳密度为45.82～53.27 t/hm2,固碳能力为5.91～6.87t/(hm2.a),高于上海城市森林平均值,但小于中国森林平均值,一定程度上受平均胸径、郁闭度及群落密度等因素影响。厂区在进行绿化建设时,应考虑选择防污且固碳能力强的植物,构建防污固碳兼有型群落,发挥植被的多元功能。     

Influence of regional development policies and clean technology adoption on future air pollution exposure

Future air pollution emissions in the year 2030 were estimated for the San Joaquin Valley (SJV) in central California using a combined system of land use, mobile, off-road, stationary, area, and biogenic emissions models. Four scenarios were developed that use different assumptions about the density of development and level of investment in transportation infrastructure to accommodate the expected doubling of the SJV population in the next 20 years. Scenario 1 reflects current land-use patterns and infrastructure while scenario 2 encouraged compact urban footprints including redevelopment of existing urban centers and investments in transit. Scenario 3 allowed sprawling development in the SJV with reduced population density in existing urban centers and construction of all planned freeways. Scenario 4 followed currently adopted land use and transportation plans for the SJV. The air quality resulting from these urban development scenarios was evaluated using meteorology from a winter stagnation event that occurred on December 15th, 2000 to January 7th 2001. Predicted base-case PM2.5 mass concentrations within the region exceeded 35 μg m^?3 over the 22-day episode. Compact growth reduced the PM2.5 concentrations by ～1 μg m^?3 relative to the base-case over most of the SJV with the exception of increases (～1 μg m^?3) in urban centers driven by increased concentrations of elemental carbon (EC) and organic carbon (OC). Low-density development increased the PM2.5 concentrations by 1–4 μg m^?3 over most of the region, with decreases (0.5–2 μg m^?3) around urban areas. Population-weighted average PM2.5 concentrations were very similar for all development scenarios ranging between 16 and 17.4 μg m^?3. Exposure to primary PM components such as EC and OC increased 10–15% for high density development scenarios and decreased by 11–19% for low-density scenarios. Patterns for secondary PM components such as nitrate and ammonium ion were almost exactly reversed, with a 10% increase under low-density development and a 5% decrease under high density development. The increased human exposure to primary pollutants such as EC and OC could be predicted using a simplified analysis of population-weighted primary emissions. Regional planning agencies should develop thresholds of population-weighted primary emissions exposure to guide the development of growth plans. This metric will allow them to actively reduce the potential negative impacts of compact growth while preserving the benefits.     

Time-series analysis of above-road particulate matter at the Caldecott Tunnel exit

On November 18, 1997, above-road particulate matter (PM) lidar (light detection and ranging) signals and heavy-duty (HD) and light-duty (LD) vehicle counts were simultaneously collected for 894 10-sec sampling periods at the Caldecott Tunnel in Orinda, CA, for the purpose of measuring the relative contributions of LD and HD vehicles to the PM lidar signal under real-world driving conditions. The relationship between the PM lidar signal and traffic activity (i.e., LD and HD traffic volumes) was examined using a time-series analysis technique, multilagged regression. The time-series model results indicate that the PM lidar signal in the current sampling period (PMt) depended on the level recorded in the previous three sampling periods (i.e., PMt-1, PMt-2, and PMt-3), the number of LD vehicles in the seventh past sampling period (LDt-7), and the number of HD vehicles measured 80 sec previous to the current sampling period (HDt-8). On a 10-sec period basis, the model results indicate that HD vehicles contributed, on average, 3 times more to above-road PM lidar signals than did LD vehicles. The observed lag in the relationship between vehicle types and the lidar signal 20 m above the road suggests that resuspended road dust, rather than tailpipe exhaust emissions, was the main source of the detected PM. Detection of road dust at such heights above the road suggests the need for investigating the processes governing the vertical transport and recycling of PM over the road as a function of vehicle dynamics under a range of meteorological conditions.     

园林绿化树种香樟叶片的含硫量动态分析

植物对一定浓度范围内的大气污染物,具有一定程度的抵抗及吸收净化作用。为了解南京市主要园林绿化树种香樟（Cinnamomum camphora）叶片吸收净化SO2的能力,选择在5个不同污染靶区,以3个不同胸径级的香樟叶片为研究对象,采用硫酸钡比浊法测定了不同季节香樟叶片的含硫量。结果表明：香樟叶片对SO2具有一定的吸收净化能力,其叶片含硫量平均为0.2160%,且其含量随分布区、生长季节及个体胸径不同差异显著;并与异域大气中SO2污染指数成一定的正相关;与个体胸径大小成显著负相关;季节间呈现出＂先降后升再降＂的动态趋势,于春秋季较高,而夏冬季较低。     

江苏水源地型水库异味物质发生风险及影响因素

为认知水源地型水库异味发生风险及其规律,本研究于异味风险高危期(夏季),对江苏17个省级水源地型水库开展了水质、浮游生物和异味物质状况调查.结果表明,本次调查的17个水库普遍存在富营养化程度偏高(如藻类生物量偏大和水体透明度偏低)的问题,约三分之一的水库出现部分水层异味物质2-甲基异莰醇(MIB)浓度超标,MIB平均浓度为(13. 7±20. 7) ng·L-1,表明江苏省水库型水源地普遍存在MIB风险;多个水库检出土臭素(GSM),但其浓度均没有超过10ng·L-1的饮用水标准浓度(最大浓度为4. 6 ng·L-1);同步水质调查及统计分析表明,MIB浓度和水体叶绿素a浓度、水体透明度、悬浮颗粒物浓度、富营养化指数等重要水质指标及浮游植物生物量(特别是蓝藻生物量)相关性显著(P 0. 05),其中MIB与叶绿素a、富营养化指数呈极显著的相关关系(P 0. 01).因此,水源地型水库的异味物质风险与水库的富营养化密切相关;实施营养盐外源输入削减、提高流域植被覆盖度、科学调控渔业养殖规模等水体富营养化控制措施是水库异味物质控制的关键.     

离子色谱法同时测定土壤中可溶性Na^、K^＋、Mg^2＋、Ca^2＋

应用离子色谱法（IC）同时测定土壤中可溶性Na^、K^＋、Mg^2＋、Ca^2＋。以CS12A阳离子交换柱分离,稀硫酸为淋洗液,电导检测器检测,对土壤中的Na^、K^＋、Mg^2＋、Ca^2＋进行同时测定。方法具有较宽的线性范围和较高的灵敏度。在0～40mg／L内呈良好的线性关系,土壤中Na^、K^＋、Mg^2＋、Ca...     

A new screening measure to identify potential carbon monoxide hotspots

To demonstrate conformity of transportation projects to National Ambient Air Quality Standards in accordance with State Implementation Plans, the U.S. Environmental Protection Agency (EPA) uses intersection level of service (LOS) as one of its major criteria for screening for potential carbon monoxide (CO) hotspots. Although intersection LOS is a measure of traffic volume, signal timing, and related congestion and delay, the assigned level reflects only the computed averaged stopped delay (ASD) per vehicle at the intersection. Thus, intersections can often operate at the same LOS but produce vastly different levels of predicted CO concentrations. For example, a two-lane approach operating at LOS D will produce very different levels of CO than a five-lane approach also operating at LOS D. This study explores the effectiveness of the LOS D criterion as a screen for identifying potential CO hotspots. The study results indicate that LOS is a poor predictor of potential CO hotspots when compared to results generated with the EPA-recommended micro-scale model CAL3QHCr. To more consistently screen out those intersections that will not be identified as CO hotspots using the micro-scale models, a new criterion, equivalent red-time vehicles (ERTV), is introduced. The modeling results using ERTV suggest that it is a more robust measure for identifying potential CO hotspots, and conversely, screening out those intersections that are not likely to be identified as hotspots using micro-scale simulation results.