Variation of mass scattering efficiencies in IMPROVE

The Interagency Monitoring of Protected Visual Environments (IMPROVE) equation used to assess compliance under the U.S. Environmental Protection Agency (EPA) Haze Rule assumes that dry mass scattering efficiencies for aerosol chemical components are constant. However, examination of aerosol size distributions and chemical composition during the Big Bend Regional Aerosol and Visibility Observational Study and the Southeastern Aerosol and Visibility Study suggests that volume and mass scattering efficiencies vary directly with increasing particle light scattering and aerosol mass concentration. This is consistent with the observation that particle distributions were shifted to larger sizes under more polluted conditions and appears to be related to aging of the aerosol during transport to remote locations.     

Determination of the organic aerosol mass to organic carbon ratio in IMPROVE samples

The ratio of organic mass (OM) to organic carbon (OC) in PM(2.5) aerosols at US national parks in the IMPROVE network was estimated experimentally from solvent extraction of sample filters and from the difference between PM(2.5) mass and chemical constituents other than OC (mass balance) in IMPROVE samples from 1988 to 2003. Archived IMPROVE filters from five IMPROVE sites were extracted with dichloromethane (DCM), acetone and water. The extract residues were weighed to determine OM and analyzed for OC by thermal optical reflectance (TOR). On average, successive extracts of DCM, acetone, and water contained 64%, 21%, and 15%, respectively, of the extractable OC, respectively. On average, the non-blank-corrected recovery of the OC initially measured in these samples by TOR was 115+/-42%. OM/OC ratios from the combined DCM and acetone extracts averaged 1.92 and ranged from 1.58 at Indian Gardens, AZ in the Grand Canyon to 2.58 at Mount Rainier, WA. The average OM/OC ratio determined by mass balance was 2.07 across the IMPROVE network. The sensitivity of this ratio to assumptions concerning sulfate neutralization, water uptake by hygroscopic species, soil mass, and nitrate volatilization were evaluated. These results suggest that the value of 1.4 for the OM/OC ratio commonly used for mass and light extinction reconstruction in IMPROVE is too low.     

Environmental cadium exposure and metabolic responses of the Nile tilapia, Oreochromis niloticus

The contamination of water by metal compounds is a worldwide environmental problem. This study was undertaken to evaluate the impact of short-term cadmium exposure on metabolic patterns of the freshwater fish Oreochromis niloticus. The fish were exposed to 320, 640, 1,280 and 2,560 microg/l sublethal concentrations of Cd++ (CdCl2) in water for 7 days. The specific activities of the enzymes phosphofructo kinase (PFK-E.C.2.7.1.11.), lactate dehydrogenase (LDH-E.C.1.1.1.27.) and creatine kinase (CKE.C.2.7.3.2.) were decreased in white muscle after cadmium treatments, indicating decreases in the capacity of glycolysis in this tissue. Cadmium exposure induced increased glucose concentration in white muscle of fish. On the other hand, cadmium exposure at sublethal concentrations increased phosphofructo kinase and LDH in red muscle of fish. Cadmium significantly decreased total protein concentrations in liver and white muscle regardless of tissue glycogen levels. The data suggest that cadmium acts as a stressor, leading to metabolic alterations similar to those observed in starvation.     

炸药驱动式爆炸管的载荷计算

目的 建立管道内冲击波参数工程预示方法,指导炸药驱动式爆炸管载荷设计和试验调试.方法 建立炸药爆炸的多介质流动数值模型,研究圆形管道内冲击波的传播规律,给出冲击波参数与炸药量、传播距离之间的变化关系,基于已有的坑道内冲击波超压预示公式,建立表征模型.结果 冲击波在管道中经过一定距离的传播后,会逐渐形成平面冲击波.随着传播距离的增加,平面冲击波的超压峰值逐渐降低,正压持续时间逐渐增大.增大炸药量可以在相同距离下获得更高超压峰值的平面冲击波,已有坑道冲击波超压预示公式同样适用于圆形管道.结论 该冲击波参数预示模型可应用于爆炸激波管载荷设计和试验调试.     

时间序列分析及Monte Carlo方法在降水预报中的应用

文章分别阐述了时间序列分析方法及Monte Carlo(蒙特卡洛)方法的基本原理和计算方法,并将其应用于降水预报的实例之中。时间序列分析是对降水资料进行观察、研究,用一定的数学方法建立预测模型,使时间序列向外延伸,从而获得序列的发展变化趋势,确定变量的预测值,精确的预报每一时段的降水量。蒙特卡洛方法是根据降水资料,提取研究区年降水量变化所蕴含的随机性和统计规律性,建立伪随机数与样品值的对应关系,从而对未来降水量进行预报,结果反映了预报时间内降水的总体特征,而不能精确到具体时间段。将这两种不同的方法用于同一地区年降水量的预报,对比结果,探其原因,分析其各自特点,进而得到更精确的预报值,对该地区水资源的研究有着重要的现实意义。     

Chemical characteristics and source apportionment of PM<Subscript>2.5</Subscript> using PCA/APCS,UNMIX, and PMF at an urban site of Delhi,India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^?3 (range 25.1–429.8 μg m^?3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ～17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.     

Air quality impacts of distributed energy resources implemented in the northeastern United States

Emissions from the potential installation of distributed energy resources (DER) in the place of current utility-scale power generators have been introduced into an emissions inventory of the northeastern United States. A methodology for predicting future market penetration of DER that considers economics and emission factors was used to estimate the most likely implementation of DER. The methodology results in spatially and temporally resolved emission profiles of criteria pollutants that are subsequently introduced into a detailed atmospheric chemistry and transport model of the region. The DER technology determined by the methodology includes 62% reciprocating engines, 34% gas turbines, and 4% fuel cells and other emerging technologies. The introduction of DER leads to retirement of 2625 MW of existing power plants for which emissions are removed from the inventory. The air quality model predicts maximum differences in air pollutant concentrations that are located downwind from the central power plants that were removed from the domain. Maximum decreases in hourly peak ozone concentrations due to DER use are 10 ppb and are located over the state of New Jersey. Maximum decreases in 24-hr average fine particulate matter (PM2.5) concentrations reach 3 microg/m3 and are located off the coast of New Jersey and New York. The main contribution to decreased PM2.5 is the reduction of sulfate levels due to significant reductions in direct emissions of sulfur oxides (SO(x)) from the DER compared with the central power plants removed. The scenario presented here represents an accelerated DER penetration case with aggressive emission reductions due to removal of highly emitting power plants. Such scenario provides an upper bound for air quality benefits of DER implementation scenarios.     

Guidance for the Performance Evaluation of Three-Dimensional Air Quality Modeling Systems for Particulate Matter and Visibility

ABSTRACT

Guidance for the performance evaluation of three-dimensional air quality modeling systems for particulate matter and visibility is presented. Four levels are considered: operational, diagnostic, mechanistic, and probabilistic evaluations. First, a comprehensive model evaluation should be conducted in at least two distinct geographical locations and for several meteorological episodes. Next, streamlined evaluations can be conducted for other similar applications if the comprehensive evaluation is deemed satisfactory. In all cases, the operational evaluation alone is insufficient, and some diagnostic evaluation must always be carried out. Recommendations are provided for designing field measurement programs that can provide the data needed for such model performance evaluations.