CO2浓度升高对半干旱区春小麦光合作用及水分生理生态特性的影响

大气CO₂浓度升高已成为世界范围内重要环境问题。为了解大气CO₂浓度升高对春小麦光合作用及水分生理生态特性的影响,在典型半干旱区定西利用开顶式气室(OTC)试验平台,以春小麦“定西24号”为供试品种,开展了CO₂浓度增加模拟试验。试验设对照(390μmol·mol^?1)、480μmol·mol^?1和570μmol·mol^?1等3个CO₂浓度(摩尔分数)梯度。结果表明:在对照和增加CO₂浓度条件下,春小麦叶片净光合速率和蒸腾速率日变化均呈“双峰型”分布,出现明显的“午休”现象;胞间CO₂浓度的日变化表现为斜“V”字型曲线;叶水势日变化呈现反抛物线曲线走向,在中午后出现水势曲线拐点。在不同生育时期内,净光合速率、气孔导度和胞间CO₂浓度均表现为开花期最大,乳熟期最小。而蒸腾速率表现为开花期最大,拔节期最小,叶片水平水分利用效率表现为孕穗期最大,乳熟期最小。随着CO₂浓度升高,春小麦叶片净光合速率、胞间CO₂浓度、水分利用效率和水势提高,气孔导度和蒸腾速率降低。与对照大气CO₂浓度相比,在480μmol·mol^?1浓度和570μmol·mol^?1浓度下,整个生育期净光合速率平均分别提高了14.68%和28.20%,气孔导度平均降低了15.29%和24.83%,胞间CO₂浓度平均提高了10.38%和26.15%,蒸腾速率平均减小了6.63%和12.41%,WUE平均增加了22.9%和46.9%。随着CO₂浓度升高,蒸腾失水减少,叶片水势不断增加,从而增强了春小麦对干旱胁迫的抵御能力。研究结果为我国半干旱区春小麦对全球气候变化下的敏感性及适应性提供理论参考。     

鸭绿江口137Cs的沉积记录及其意义

根据2013、2014、2018年鸭绿江口16个柱状样的¹³⁷Cs沉积记录,分析了其垂向分布特征,划分了¹³⁷Cs 的4种沉积类型。根据柱状样¹³⁷Cs蓄积量较高、沉积连续、沉积过程清楚、最大蓄积峰对应1963年的特征初步确定了适合河口不同沉积状态的4个“参考”剖面,并与理想状态的大气沉降曲线进行了对比分析,显示鸭绿江口参考剖面的¹³⁷Cs沉积记录与大气沉降量（输入函数）曲线基本吻合。1963年的主计年时标涵盖大部分柱状样,层位清楚、容易识别、可以信赖。鸭绿江口存在疑似1975年和1986年¹³⁷Cs的计年时标,但用于计年时需谨慎。1986年以后大多数沉积记录显示了¹³⁷Cs沉积迅速降低的趋势,其他少部分柱状样的¹³⁷Cs蓄积峰是动力过程混合或扩散作用的结果,也不排除陆源输送。表层沉积物大多数站位检测不出¹³⁷Cs,说明近期陆源¹³⁷Cs的输送量微乎其微,个别站位表层中较多的¹³⁷Cs来源有待进一步研究。     

响应面法优化菌株Bacillus sp.W77酯酶发酵条件

为开发适应性好的工业用酶,从深圳福田红树林自然保护区土壤中分离纯化获得一株产耐高温嗜碱性酯酶的菌株,通过形态学和分子生物学初步鉴定该菌株为芽孢杆菌属(Bacillus sp.),命名为Bacillus sp.W77;对所产的粗酶液进行酶活测定,发现该菌产的酯酶的最适反应温度是50℃,最适pH为8.0,且在碱性条件下较稳定;采用响应面法(Response surface methodology)对土壤菌株Bacillus sp.W77的产酯酶条件进行了优化,酵母提取物6.67 g/L,磷酸氢二钾0.56 g/L,硫酸镁0.36 g/L时,此时预测的最大酯酶活力的D405 nm值为1.266,在最佳产酶条件下,优化后酯酶活力的D405 nm值由0.829提高到1.235,实际值达到理论预测值的97.5%.     

无锡冬季和春季大气中细粒子化学组分及其特性分析

本研究对无锡冬（2011年1月）春（2011年5月）两季PM2.5、PM10颗粒物浓度进行了传统的膜采样及离线检测分析,并运用大气气体/气溶胶水溶性离子在线收集及分析（GAC-IC）系统对PM2.5颗粒物中水溶性无机离子（WSⅡ）进行了在线检测,时间分辨率为30 min.无锡冬、春两季PM2.5的浓度分别为108.15±41.76 μg·m-3 和84.40±26.74 μg·m-3,其PM2.5/PM10比值分别为0.81±0.07和0.78±0.07,有较强的二次气溶胶生成过程.铵可用性指数（J冬季=101.2%±22.3%,J春季=79.5%±20.2%）分析表明冬季无锡大气颗粒物中铵（NH4+）相对比较富余,而春季则出现铵（NH4+）亏损现象,春季光化学反应更为活跃,硫氧化率（SOR）由冬季的0.15±0.05增至春季的0.35±0.13,硫酸盐（SO42-）浓度增加明显,导致铵（NH4+）相对不足.硫氧化率（SOR）没有明显的季节变化,冬、春两季均为0.15.细粒子中的WSⅡ与气态污染物、气象因子、硫氧化率（SOR）和氮氧化率（NOR）等的主成分分析表明无锡大气光化学反应与污染物的其他来源,例如工业源、交通移动源、生物质燃烧源等,有很好的协同作用,共同推高了大气中颗粒物的浓度.观测期间同时测得冬季PM2.5颗粒中有机碳（OC）与元素碳（EC）浓度之间有较好的相关性（R2=0.839）,两者有一个共同的主导源,而春季来源则比较复杂,两者相关性较差;二次有机碳（SOC）的半定量分析表明春季大气中有机气溶胶的形成有较强的二次转化过程.     

高浓度含油废水中不同组分烃的生物强化去除特性

为探究石油烃降解菌群对高浓度含油废水中不同组分烃的生物降解特性,向含油水相中接种石油烃降解菌群LW-10(Accession number: SRR15082184)进行降解实验。利用GC-MS研究了LW-10对原油中不同组分烃的降解性能,采用流式细胞术检测降解体系中的菌量变化。利用qPCR技术对控制不同组分烃降解的关键基因进行检测。结果表明,原油浓度为5000 mg·L⁻¹的含油废水中接种LW-10降解17 d,对原油中烷烃和多环芳烃组分的降解率分别为96.7%和28.4%。体系中的降解菌总浓度与高活性菌浓度由接种时的1.0×10⁸ cfu·mL⁻¹增加至2.1×10⁹ cfu·mL⁻¹和8.3×10⁸ cfu·mL⁻¹。检测的3种石油烃降解功能基因中,烷烃单加氧酶基因alkB2拷贝数由1.06×10⁸ copy·mL⁻¹变为2.84×10⁸ copy·mL⁻¹;芳烃双加氧酶基因Ahd由1.06×10⁸ copy·mL⁻¹降低至1.65×10⁷ copy·mL⁻¹;氧化还原酶基因PA4513由4.09×10⁶ copy·mL⁻¹增加增加至9.26×10⁸ copy·mL⁻¹。结果表明降解菌群LW-10对含油废水中的烷烃组分具有高效降解能力,对多环芳烃组分的降解能力较差。LW-10在降解石油烃过程中通过同化作用发生增殖,不同组分烃的降解效果与石油烃降解功能基因之间存在正相关关系。     

选矿循环水处理研究

氰化尾渣浮选硫精矿过程中,选矿水长时间循环使用,导致选矿水中的的黄药、氰化物及重金属络合物等不断富集,影响了硫精矿浮选效率.为解决这一问题,采用臭氧氧化+碟管式反渗透+机械式蒸汽压缩技术,对选矿循环水进行处理,减少水中CODcr、氰化物、TDS,提高硫精矿回收率,降低生产成本.     

Surface modelling of global terrestrial ecosystems under three climate change scenarios

A high accuracy and speed method (HASM) of surface modelling is developed to find a solution for error problem and to improve computation speed. A digital elevation model (DEM) is established on spatial resolution of 13.5 km × 13.5 km. Regression formulations among temperature, elevation and latitude are simulated in terms of data from 2766 weather observation stations scattered over the world by using the 13.5 km × 13.5 km DEM as auxiliary data. Three climate scenarios of HadCM3 are refined from spatial resolution of 405 km × 270 km to 13.5 km × 13.5 km in terms of the regression formulations. HASM is employed to simulate surfaces of mean annual bio-temperature, mean annual precipitation and potential evapotranspiration ratio during the periods from 1961 to 1990 (T₁), from 2010 to 2039 (T₂), from 2040 to 2069 (T₃), and from 2070 to 2099 (T₄) on spatial resolution of 13.5 km × 13.5 km. Three scenarios of terrestrial ecosystems on global level are finally developed on the basis of the simulated climate surfaces. The scenarios show that all polar/nival, subpolar/alpine and cold ecosystem types would continuously shrink and all tropical types, except tropical rain forest in scenario A1Fi, would expand because of the climate warming. Especially at least 80% of moist tundra and 22% of nival area might disappear in period T₄ comparing with the ones in the period T₁. Tropical thorn woodland might increase by more than 97%. Subpolar/alpine moist tundra would be the most sensitive ecosystem type because its area would have the rapidest decreasing rate and its mean center would shift the longest distance towards west. Subpolar/alpine moist tundra might be able to serve as an indicator of climatic change. In general, climate change would lead to a continuous reduction of ecological diversity.     

Scenarios of major terrestrial ecosystems in China

The spatial pattern and mean-center shift of major terrestrial ecosystems, termed Holdridge Life Zones (HLZ), during the periods from 1961 to 1990 (T1), from 2010 to 2039 (T2), from 2040 to 2069 (T3) and from 2070 to 2099 (T4) were analyzed by combining the zonal patterns of climatic change in China and the climatic change scenarios of HadCM2 and HadCM3. The results showed that nival area would decrease rapidly with temperature increase in the future. HadCM2 and HadCM3 predicted that the nival areas might disappear in 552 years and 204 years, respectively. Using both HadCM2 and HadCM3, the five HLZ types with the largest areal extent are nival zone, cool temperate moist forest, warm temperate moist forest, subtropical moist forest and boreal wet forest, which collectively account for more than 50% of China's land mass. Among these five HLZ types, nival zone, warm temperate moist forest and boreal wet forest would decrease continuously, whereas subtropical moist forest and cool temperate forest would increase continuously during the four periods. HLZ diversity and patch connectivity would increase continuously in the 21st century. The shift distances of mean centers of HLZ types simulated using HadCM3 were markedly greater than those simulated using HadCM2, in general. The results from both HadCM2 and HadCM3 showed that boreal wet forest, subtropical moist forest, tropical dry forest, warm temperate moist forest and subtropical wet forest had bigger shift ranges, indicating that these HLZ types are more sensitive to the climatic change scenarios of HadCM2 and HadCM3.