Exploring the relationship between vegetation spectra and eco-geo-environmental conditions in karst region, Southwest China

Remote sensing of local environmental conditions is not accessible if substrates are covered with vegetation. This study explored the relationship between vegetation spectra and karst eco-geo-environmental conditions. Hyperspectral remote sensing techniques showed that there were significant differences between spectral features of vegetation mainly distributed in karst and non-karst regions, and combination of 1,300- to 2,500-nm reflectance and 400- to 680-nm first-derivative spectra could delineate karst and non-karst vegetation groups. Canonical correspondence analysis (CCA) successfully assessed to what extent the variation of vegetation spectral features can be explained by associated eco-geo-environmental variables, and it was found that soil moisture and calcium carbonate contents had the most significant effects on vegetation spectral features in karst region. Our study indicates that vegetation spectra is tightly linked to eco-geo-environmental conditions and CCA is an effective means of studying the relationship between vegetation spectral features and eco-geo-environmental variables. Employing a combination of spectral and spatial analysis, it is anticipated that hyperspectral imagery can be used in interpreting or mapping eco-geo-environmental conditions covered with vegetation in karst region.     

Risk assessment of heavy metals in road and soil dusts within PM2.5, PM10 and PM100 fractions in Dongying city, Shandong Province, China

15 road and 14 soil dust samples were collected from an oilfield city, Dongying, from 11/2009-4/2010 and analyzed by inductively coupled plasma-mass spectroscopy (ICP-MS) for V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd and Pb within PM(2.5), PM(10) and PM(100) fractions synchronously. Metal concentrations, sources and human health risk were studied. Results showed that both soil and road dust exhibited higher values for Mn and Zn and lower values for Co and Cd for the three fractions. Mass concentration ratios of PM(2.5)/PM(10) and PM(10)/PM(100) for metals in road and soil dust indicate that most of the heavy metals tend to concentrate in fine particles. Geoaccumulation index and enrichment factors analysis showed that Cu, Zn and Cd exhibited moderate or heavy contamination and significant enrichment, indicating the influence of anthropogenic sources. Vanadium, Cr, Mn and Co were mostly not enriched and were mainly influenced by crustal sources. For Ni, As and Pb, they ranged from not enriched to moderately enriched and were influenced by both crustal materials and anthropogenic sources. The conclusions were confirmed by multivariate analysis methods. Principle component analysis revealed that the major sources were vehicle emission, industrial activities, coal combustion, agricultural activities and crustal materials. The risk assessment results indicated that metal ingestion appeared to be the main exposure route followed by dermal contact. The most likely cause for cancer and other health risks are both the fine particles of soil and road dusts.     

Chemical compositions and sources of atmospheric PM10 in heating, non-heating and sand periods at a coal-based city in northeastern China

Mass concentrations and chemical components (18 elements, 9 ions, organic carbon [OC] and elemental carbon [EC]) in atmospheric PM(10) were measured at five sites in Fushun during heating, non-heating and sand periods in 2006-2007. PM(10) mass concentrations varied from 62.0 to 226.3 μg m(-3), with 21% of the total samples' mass concentrations exceeding the Chinese national secondary standard value of 150 μg m(-3), mainly concentrated in heating and sand periods. Crustal elements, trace elements, water-soluble ions, OC and EC represented 20-47%, 2-9%, 13-34%, 15-34% and 13-25% of the particulate matter mass concentrations, respectively. OC and crustal elements exhibited the highest mass percentages, at 27-34% and 30-47% during heating and sand period. Local agricultural residuals burning may contribute to EC and ion concentrations, as shown by ion temporal variation and OC and EC correlation analysis. Heavy metals (Cr, Ni, Zn, Cu and Mn) from coal combustion and industrial processes should be paid attention to in heating and sand periods. The anion/cation ratios exhibited their highest values for the background site with the influence of stationary sources on its upper wind direction during the sand period. Secondary organic carbon were 1.6-21.7, 1.5-23.0, 0.4-17.0, 0.2-33.0 and 0.2-21.1 μg m(-3), accounting for 20-77%, 44-88%, 4-77%, 8-69% and 4-73% of OC for the five sampling sites ZQ, DZ, XH, WH and SK, respectively. From the temporal and spatial variation analysis of major species, coal combustion, agricultural residual burning and industrial emission including dust re-suspended from raw material storage piles were important sources for atmospheric PM(10) in Fushun at heating, non-heating and sand periods, respectively. It was confirmed by principal component analysis that coal combustion, vehicle emission, industrial activities, soil dust, cement and construction dust and biomass burning were the main sources for PM(10) in this coal-based city.     

农药厂周边有机磷农药在生物体中残留的检测方法研究

对中美两国固定源测试技术体系进行总结并按照辅助类参数、烟气类污染物、烟尘类污染物、有机类污染物、元素及卤化物、在线监测规范进行分类并比较,指出两国测试体系的异同。结合目前形势指出中国烟尘、烟气及VOCs类污染物监测体系面临问题并提出建议。     

西宁市典型开放源颗粒物粒径组成特征分析

采用BT-9300S激光粒度仪分析了西宁市道路尘、扬尘、土壤尘、建筑尘4种典型开放源的粒径组成。结果表明,4种类型尘中大粒径颗粒物占主导地位,粒径大于10 μm颗粒占到全部颗粒的73.80%以上,可吸入颗粒物的含量仅占7.06%～26.20%;建筑尘的细颗粒物含量最高,粒径小于2.5、1 μm的颗粒含量分别为8.36%±4.25%、2.42%±1.02%;道路尘的细颗粒物含量最低,粒径小于2.5、1 μm的颗粒含量分别为2.30%±0.94%、0.73%±0.28%;4种类型尘的体积平均直径、面积平均直径、中位直径分别在37.70～87.99 μm、8.50～23.53 μm、28.95～74.98 μm之间,其中道路尘的3种粒径参数最大,建筑尘最小;开放源颗粒物的粒度分布曲线主要呈头长尾短的不对称单峰分布,累积频率曲线为两段式,存在较为明显的拐点。     

高效率颗粒物微物理模型简介与重污染过程应用分析

中国细颗粒物(PM2.5)导致的空气污染和雾霾天气问题越来越突出,在低层对流层中很多地方都有显著的二次颗粒物生成过程,因此对颗粒物物理化学转化过程的研究具有重要意义,其转化过程对空气质量模式模拟和预报的准确性有重要影响。高效率颗粒物微物理(APM)模型经过近20多年的研究和发展,在全球化学传输模型(GEOS-Chem)、区域性气象和化学预报模型(WRF-Chem)通用地球系统模型(CESM-CAM5)等气象及环境空气质量预报模型中取得了很好的应用验证,能够在全球/区域等不同尺度对粒子生成、长大、凝聚、消除等微物理过程以及气溶胶光学厚度(AOD)、直接/间接辐射强迫等进行模拟。应用GEOS-Chem-APM模式模拟了2014年2月京津冀区域的重污染过程。结果显示,湿度模拟的准确性对其他物理和污染物浓度等模拟结果有重要作用;2月20—26日的重污染过程模拟结果与实际观测较为吻合,主要污染特点是较高的湿度(90%以上),同时,二次颗粒物和包裹了二次物种的一次颗粒物(黑碳/有机碳)是低能见度的最大贡献者。     

显色条件对纳氏试剂分光光度法测定水中氨氮的影响

氨氮是水质监测和评价的重要指标之一。本文探讨了纳氏试剂光度法测定水中氨氮时显色温度和显色时间对测定结果的影响,并从空白测定、显色速率及校准曲线等方面进行了分析,提出了对测定方法的改进建议。     

Understanding the Price Dynamics in the Jiangsu SO2 Emissions Trading Program in China: A Multiple Periods Analysis

Because emissions permits can be considered to be a pseudo-commodity, the permit price in the emissions trading markets has already attracted great interest from the economic literature. This research took the Jiangsu sulfur dioxide (SO₂) emissions trading program in China as a case study to examine the price dynamics over the next 10 years (2011–2020) based on Jiangsu’s new SO₂ emissions trading policy design. An adaptive agent-based simulation model was developed to estimate the price dynamics as well as the impact of energy price, policy design, and new environmental regulation on the permit price. The results showed that the equilibrium price of the Jiangsu SO₂ emissions trading market is approximately 4.20 CNY/kg, and the permit price will fluctuate around this price if the other conditions are not changed. If the coal price increases during 2011–2016, the permit price will decline to 2.79 CNY/kg by 2020 under China’s current coal–electricity price mechanism. In addition, the banking mechanism will smooth the price fluctuations and the average permit price will be generally higher when banking is not allowed. Finally, the stricter environmental regulation will reduce the market supply of permits and will raise the permit price. According to China’s potential new SO₂ discharge standard, the permit price will jump to 11 CNY/kg. The quantification of the permit price dynamics can help power plants to make decisions on emissions trading.     

季节性Kendall检验分析湘江长沙段水质变化趋势

季节性Kendall检验是一种广泛应用于河流水质变化趋势分析的非参数检验。以湘江长沙段三汊矶断面2001—2011年水质监测结果为样本,运用季节性Kendall检验分析湘江长沙段水质变化趋势及影响因素,结果表明:氨氮浓度呈显著上升趋势,总磷浓度呈高度显著上升趋势,总镉、总砷浓度呈高度显著下降趋势,湘江长沙段水质主要受城市生活、工业和农业面源污染物排放的影响,河水流量对水质的影响相对较小。