Sensitivity analyses of woody species exposed to air pollution based on ecophysiological measurements

GOAL, SCOPE AND BACKGROUND: Air pollution has been of a major problem in the Pearl River Delta of south China, particularly during the last two decades. Emissions of air pollutants from industries have already led to damages in natural communities and environments in a wide range of the Delta area. Leaf parameters such as chlorophyll fluorescence, leaf area (LA), dry weight (DW) and leaf mass per area (LMA) had once been used as specific indexes of environmental stress. This study aims to determine in situ if the daily variation of chlorophyll fluorescence and other ecophysiological parameters in five seedlings of three woody species, Ilex rotunda, Ficus microcarpa and Machilus chinensis, could be used alone or in combination with other measurements for sensitivity indexes to make diagnoses under air pollution stress and, hence, to choose the correct tree species for urban afforestation in the Delta area. METHODS: Five seedlings of each species were transplanted in pot containers after their acclimation under shadowing conditions. Chlorophyll fluorescence measurements were made in situ by a portable fluorometer (OS-30, Opti-sciences, U.S.A). Ten random samples of leaves were picked from each species for LA measurements by area-meter (CI-203, CID, Inc., U.S.A). DW was determined after the leaf samples were dried to a constant weight at 65 degrees C. LMA was calculated as the ratio of DW/LA. Leaf N content was analyzed according to the Kjeldhal method, and the extraction of pigments was carried out according Lin et al. RESULTS AND DISCUSSION: The daily mean Fv/Fm (Fv is the variable fluorescence and Fm is the maximum fluorescence) analysis showed that Ilex rotunda and Ficus microcarpa were more highly resistant to pollution stress, followed by Machilus chinensis, implying that the efficiency of photosystem II in I. rotunda was less affected by air pollutants than the other two species. Little difference in daily change of Fv/Fm in I. rotunda between the polluted and the clean site was also observed. However, a relatively large variation of Fv/Fm appeared in the other two species, particularly in M. chinensis, suggesting that they were more sensitive to air pollutants than I. rotunda. The mean LA was reduced for all species growing at the polluted site. The mean LMA for all species exceeded the sclerophylly threshold given by Cowling and Campbell and increased for those under pollution stress, which could be explained as one of the acclimation strategies for plants to air pollution stress. Little difference in leaf chlorophyll content was observed in F. microcarpa and M. chinensis, while remarkable differences were found in I. rotunda growing at the polluted and the clean site. Content of leaf carotenoids was largely reduced in I. rotunda growing at the polluted site, but increased in F. microcarpa and M. chinensis, compared with plants growing at the clean site. Plants growing at the clean site had a lower leaf N content than those growing at the polluted site. In addition, species with a higher resistance to pollution stress showed less difference in leaf N content than those sensitive species. CONCLUSION: Based on Fv/Fm measurements of the three woody species, I. rotunda showed the highest resistance to air pollutants from ceramic industries, followed by F. microcarpa. M. chinensis was the most sensitive species to air pollution, had lowest capacities to cope with the air pollution stress, which was consistent with visual injury symptoms observed in the crown profiles of plants at the polluted site. Fv/Fm, LAM, LA, leaf pigments and N content could be used alone or in combination to diagnose the extent of the physiological injury. The ratio of Fv/Fm, however, was the best and most effective parameter. RECOMMENDATION AND OUTLOOK: Tree species which have higher air-pollutant resistance, as diagnosed by such ecophysiological parameters, should be considered first and planted widely for urban afforestation or forest regeneration in areas where the forest was seriously degraded or forest health was markedly effected by the same kind of air pollutants.     

Biomonitoring seasonal variation of urban air polycyclic aromatic hydrocarbons (PAHs) using Ficus benghalensis leaves

Temporal and seasonal variations of polycyclic aromatic hydrocarbons (PAHs) concentrations in leaves of Ficus benghalensis were investigated in Varanasi city (India). Leaf samples were collected from six sites from urban area of Varanasi and from a control site. PAH extraction was done by sonication in dichloromethane-acetone and quantification by GC-MS. In January total leaf PAHs concentrations at all the urban sites were twice higher as compared to other season's viz. summer and rainy. In contrast, at the control site leaf PAHs concentrations showed lower values than urban sites. The maximum concentrations of total PAHs in winter were due to the medium molecular weight PAHs which increases with respect to both low and high molecular weight PAHs. The temporal variation of medium molecular weight PAHs was similar both at the urban and remote sites. These results support biomonitoring ability of Ficus benghalensis leaves to temporal variations in PAHs contamination.     

基于地震波法的底板破坏区域探测技术及应用

针对煤矿煤层底板采空区域不明确的问题,为了确定采空区的精确范围以及内部状态,采用物探的矿井反射地震波探测技术,首先利用地质探测仪对地震波波形进行数据采集,并进行数据分析以及波形的反演计算,最终根据波形的形状和频率确定底板破坏情况;其次将底板破坏区域分为上位层破碎带和下位层破碎带;最后在现场采用底板钻探的方法对地震波探测技术进行了验证。结果表明反射地震波探测技术得到的结果接近于钻探结果,采用反射地震波探测技术可以较精确判断底板采空区破坏范围。     

BP神经网络在城市建成区面积预测中的应用——以江苏省为例

城市建成区规模的迅速扩张是目前江苏省土地利用变化中的一个显著特点，其面积从1985年的426 km2扩大到2003年的2 200 km2，平均年增加98.56 km2。城市建成区规模的扩张受到社会、经济、人口等多种因素的影响，用传统方法对其进行预测比较困难。鉴于BP神经网络在非线性领域预测中的广泛应用，以江苏省为研究对象，构建一个11-3-1结构的BP神经网络预测模型，以1985~2001年和2002年的相关数据作为模型的训练和测试样本，以2003年的社会、经济数据作为网络的预测输入，对该年的建成区面积进行预测。结果表明，BP神经网络预测结果与实际面积的相对误差为3.96%，其预测精度与多元回归预测模型相比有较大改善。     

模拟沼气池厌氧预处理南方丘陵农村厕所黑水的效能

研究了单级和二级模拟沼气池厌氧预处理南方丘陵农村厕所黑水的效能。结果表明,当进水TCOD和SCOD平均浓度分别为862和718 mg/L,HRT分别为12、24、36和72 h时,稳定期各单级模拟沼气池对TCOD的平均去除率分别为12.5%、57.5%、60.8%和67.1%;对SCOD的平均去除率分别为-15.7%、53.6%、55.3%和64.7%,当HRT为72 h时,二级模拟沼气池与单级模拟沼气池相比,其对TCOD和SCOD的平均去除率分别提高了6.4%和8.9%,表明HRT为72 h时,有较好的去除效能。二者对厕所黑水均有较好的去除效能,但二级模拟沼气池稍优于单级模拟沼气池。考虑经济性,HRT为72 h的单级模拟沼气池可优选作为农村厕所黑水厌氧预处理的核心生物单元,与后续人工湿地等生态处理装置组合。     

上海高温和低温气候变化特征及其影响因素

基于上海11个气象站逐日最高、最低气温、降水资料和西太平洋副热带高压(简称副高,下同)环流指数,分析了上海夏季高温和冬季低温的气候变化特征及其影响因素。结果表明,1873～2007年,上海高温日数表现为少-多-少-多的年代际变化,低温日数则表现为多-少的年代际变化。2001～2007年,上海年均高温日数、各级高温过程数和高温过程日数都最多,低温日数、低温过程数和低温过程日数都最少。1960～2007年,上海每年高温日数与当年夏季副高面积和强度指数显著正相关,低温日数与当年冬季副高面积和强度指数显著负相关。降水对上海极端气温有一定的缓解作用,上海高温日数与夏季降水量弱显著负相关,低温日数与冬季降水量显著负相关。上海高温过程数受城市化影响较大,其时间变化具有明显的城郊差异,低温过程数则受城市化影响较小。     

近三十年云南九大高原湖泊水面面积遥感变化监测

云南省九大高原湖泊对于云南省社会经济可持续发展具有极其重要的意义。利用30 m分辨率的Landsat系列遥感数据和1.5 m分辨率的SPOT6/7遥感数据分别对云南省九大高原湖泊1989,1993,2000,2007,2015年的湖面面积进行了动态监测。结果表明:云南省九大高原湖泊在1989~2015年间总体上较为稳定,湖体湖面面积共减少了约41 km~2(约4%),但各湖变化差异较大。杞麓湖和异龙湖湖面面积持续快速萎缩,至2015年异龙湖已萎缩了1989年湖体湖面面积的40%。其中异龙湖萎缩的主要原因是干旱和围湖造田,而滇池变化波动较大,原因主要在于工业发展及工程治理。通过对同期的Landsat 8OLI数据与SPOT6/7数据解译的杞麓湖和异龙湖湖面面积对比发现不同空间分辨率的解译结果有较为明显差异(2.8%和1.7%),表明在采用多源遥感数据进行湖泊面积解译时需要考虑不同空间分辨率的影响。     

基于遥感和信息熵的城乡结合部范围界定——以荆州市为例

城乡结合部是城市与农村相互结合的特殊经济地理单元,是城市快速扩张的重点区域,受城市与农村的双重影响,而目前城乡结合部范围不明确,确定方法以定性为主。针对这一特点,以信息熵理论为基础,结合分析城乡结合部土地利用特征,建立了土地利用信息熵模型。并以荆州市为例,以2000年10月ETM+影像为基础数据源,在ArcGIS和ERDAS Imagine软件的支持下,应用土地利用信息熵模型,分析熵值分布特点,最后采用突变点检测的方法,以熵值60和30确定荆州市城乡结合部的内外边界。得到荆州市城乡结合部的面积为124.4 km2,大致包括25个行政村。比较表明,该方法划分精度较高、实时性强。但若能采用更高分辨率的遥感影像并结合其他模型,会使划分精度进一步提高     

黑土区城郊耕地重金属污染空间扩散机制

城郊复杂环境条件下的耕地土壤重金属污染空间扩散机制是落实土壤污染源头防控和保障黑土地质量安全的基础.针对以往溯源研究中污染源头难定位和扩散趋势不明确等问题,以长春市城郊地区为例,以耕地土壤As、Pb、Hg和Cd元素为研究对象,采用近邻传播（AP）算法和空间自回归的扩散格局-驱动因素组合分析法尝试揭示黑土区城郊耕地重金属污染空间扩散机制.结果表明,ω（As）和ω（Cd）均值分别为39.35mg ·kg^-1和0.183 mg ·kg^-1,累积水平较高.内梅罗指数显示研究区有52.38%的耕地已出现轻度污染.AP算法识别出As存在3个影响幅度相似的潜在污染源地,均位于远离城市的典型农耕区;Pb元素的2个潜在污染源地集中分布于范家屯镇附近的工业区;Hg和Cd元素的扩散格局复杂,尤其是Cd元素,呈现多地并发的污染扩散特征.空间滞后模型表明,As元素的空间扩散格局和农药施用强度有关;Cd元素主要受土壤类型和设施农业布局的制约;Pb元素受区域城镇化和工业化发展的影响;Hg元素和区域污染迁移条件相关.污染调蓄功能未对4种元素的空间扩散格局产生显著影响.研究丰富了耕地重金属污染的空间分析理论和方法,对落实城郊黑土地的污染源头防控具有科学意义.     

Enhancing sensitivity of microbial fuel cell sensors for low concentration biodegradable organic matter detection: Regulation of substrate concentration, anode area and external resistance

The relatively low sensitivity is an important reason for restricting the microbial fuel cell (MFC) sensors’ application in low concentration biodegradable organic matter (BOM) detection. The startup parameters, including substrate concentration, anode area and external resistance, were regulated to enhance the sensitivity of MFC sensors. The results demonstrated that both the substrate concentration and anode area were positively correlated with the sensitivity of MFC sensors, and an external resistance of 210 Ω was found to be optimal in terms of sensitivity of MFC sensors. Optimized MFC sensors had lower detection limit (1 mg/L) and higher sensitivity (Slope value of the linear regression curve was 1.02), which effectively overcome the limitation of low concentration BOM detection. The essential reason is that optimized MFC sensors had higher coulombic efficiency, which was beneficial to improve the sensitivity of MFC sensors. The main impact of the substrate concentration and anode area was to regulate the proportion between electrogens and nonelectrogens, biomass and living cells of the anode biofilm. The external resistance mainly affected the morphology structure and the proportion of living cells of the anode. This study demonstrated an effective way to improve the sensitivity of MFC sensors for low concentration BOM detection.