抗生素在环境中的迁移转化及生物效应研究进展

抗生素被长期大量地使用于人和动物的疾病治疗,同时作为饲料添加剂长期使用于畜牧业及水产养殖业。然而,大部分抗生素不能完全被机体吸收,大量的抗生素以原形或代谢物形式经由病人和禽畜粪尿排入环境,经不同途径进入土壤和水体,从而造成环境污染。多项研究显示在城镇废水和地表水中检测到了抗生素的存在,但关于抗生素在环境中的迁移转化及生物效应等研究资料很少。环境中的抗生素会对微生物、水生生物、土壤生物和植物等产生危害,并产生大量耐药菌,影响禽畜等的正常生长,进而对人类健康及整个生态系统构成威胁。为评估抗生素在环境中潜在的危害,本文就抗生素在环境中的迁移转化以及生物效应等多方面进行综述,并提出了今后研究的方向。     

提升高校环境教育效果的对策

本文论证了高校开展环境教育的必要性,总结了高校环境教育的现状,在分析导致高校环境教育效果差强人意的原因后,为提升高校环境教育效果,提出包括立法在内的一系列对策.     

陕西关中地区旅游流"井喷效应"的时空演变规律

旅游流"井喷现象"是特殊时段旅游流时空分布的特殊现象之一,其时空分布规律研究有助于旅游目的地的科学管理参照.选取关中地区旅游资源丰富的西安、宝鸡、华山三地作为案例,建立"黄金周"客流周内波动指数R,周内分布偏度指数G,并使用相关分析和Pearson相关系数,分析陕西关中地区特殊时段内旅游流"井喷效应"的时空演变规律.结果显示,在假日制度时间约束下,旅游流呈现"井喷现象"显著,一级旅游目的地城市的旅游资源属性、周边地区旅游资源配置和区位交通状况共同影响着游客的空间选择行为,从而影响区域旅游流的时间和空间分布.     

Forecasting population trend from the scaling pattern of occupancy

Forecasting the temporal trend of a focal species, its range expansion or retraction, provides crucial information regarding population viability. To this end, we require the accumulation of temporal records which is evidently time consuming. Progress in spatial data capturing has enabled rapid and accurate assessment of species distribution across large scales. Therefore, it would be appealing to infer the temporal trends of populations from the spatial structure of their distributions. Based on a combination of models from the fields of range dynamics, occupancy scaling and spatial autocorrelation, here I present a model for forecasting the population trend solely from its spatial distribution. Numerical tests using cellular automata confirm a positive correlation, as inferred from the model, between the temporal change in species range sizes and the exponent of the power-law scaling pattern of occupancy. The model is thus recommended for rapid estimation of species range dynamics from a single snapshot of its current distribution. Further applications in biodiversity conservation could provide a swift risk assessment, especially, for endangered and invasive species.     

Integrating soil carbon cycling with that of nitrogen and phosphorus in the watershed model SWAT: Theory and model testing

In this paper we describe and test a sub-model that integrates the cycling of carbon (C), nitrogen (N) and phosphorus (P) in the Soil Water Assessment Tool (SWAT) watershed model. The core of the sub-model is a multi-layer, one-pool soil organic carbon (S_C) algorithm, in which the decomposition rate of S_C and input rate to S_C (through decomposition and humification of residues) depend on the current size of S_C. The organic N and P fluxes are coupled to that of C and depend on the available mineral N and P, and the C:N and N:P ratios of the decomposing pools. Tillage explicitly affects the soil organic matter turnover rate through tool-specific coefficients. Unlike most models, the turnover of soil organic matter does not follow first order kinetics. Each soil layer has a specific maximum capacity to accumulate C or C saturation (S_x) that depends on texture and controls the turnover rate. It is shown in an analytical solution that S_x is a parameter with major influence in the model C dynamics. Testing with a 65-yr data set from the dryland wheat growing region in Oregon shows that the model adequately simulates the S_C dynamics in the topsoil (top 0.3 m) for three different treatments. Three key model parameters, the optimal decomposition and humification rates and a factor controlling the effect of soil moisture and temperature on the decomposition rate, showed low uncertainty as determined by generalized likelihood uncertainty estimation. Nonetheless, the parameter set that provided accurate simulations in the topsoil tended to overestimate S_C in the subsoil, suggesting that a mechanism that expresses at depth might not be represented in the current sub-model structure. The explicit integration of C, N, and P fluxes allows for a more cohesive simulation of nutrient cycling in the SWAT model. The sub-model has to be tested in forestland and rangeland in addition to agricultural land, and in diverse soils with extreme properties such high or low pH, an organic horizon, or volcanic soils.     

苗期棉花对向日葵列当种子萌发诱导作用初探

以5个推广棉花（Gossypium hirsutum L.）品种（中棉所63、中棉所57、中棉所47、中棉所44和中棉所41）为研究对象,利用盆栽试验分别采集棉花苗期3个时期（二叶一心、四叶一心和六叶一心期）的根际土和植株样品,并用其甲醇浸提测试对向日葵列当（Orobanche cumana Wallr.）种子的发芽率。结果表明,根际土、植株样（根、茎和叶）甲醇浸提液诱导种子发芽率高低顺序为根际土〉根〉茎〉叶,表明棉花的根际土和根的甲醇提取液对向日葵列当种子的萌发诱导作用较强。3个时期中,二叶一心期诱导向日葵列当的发芽在品种之间不存在显著性差异,表现为较稳定的诱导种子萌发作用。综合得出,棉花二叶一心期的根际土和根的甲醇提取液对向日葵列当种子萌发的诱导作用较强,二叶一心期为棉花作为＂诱捕作物＂生物防除寄生杂草提供科学依据。     

磁暴对沿海核电站变压器安全影响的研究

磁暴产生的地磁感应电流(GIC)直接损伤变压器和间接干扰继电保护等设备,强磁暴可能威胁到电网的安全运行。为探明磁暴对沿海核电站变压器的影响,对第23太阳周峰年强磁暴侵害广东岭澳核电站、江苏上河变电站的GIC测量数据,以及西北陕甘青宁750 kV电网计算数据进行统计分析,研究沿海核电站与内陆变电站变压器GIC大小及其差异原因。结果表明,由于受海岸效应现象的影响,沿海核电站的变压器更容易遭受磁暴的侵害。在此基础上,对极端磁暴的可能危害、灾害风险以及沿海核电站的磁暴灾害进行评估,并建议核电站选址和变压器选型时应评估磁暴的影响。     

环境规制影响资源型城市绿色全要素生产率的途径与政策建议

环境规制对资源型城市绿色全要素生产率是否具有推动作用,通过何种路径驱动以及是否存在城市类型异质性有待进一步理清。本文选取2004—2019年中国113座资源型城市的面板数据,利用非径向、非角度的SBM模型与GML指数对资源型城市绿色全要素生产率进行测算,随后通过构建多重中介效应模型实证检验了科技创新、外商直接投资和产业结构优化在环境规制影响绿色全要素生产率的传导机制及其在城市类型间的异质性。研究表明：（1）从全样本回归结果看,环境规制对资源型城市绿色全要素生产率的作用系数显著为正,产业结构优化和外商直接投资均发挥了显著的正向中介效应,而科技创新表现为间接抑制作用;在非资源型城市中,三类中介效应均不显著。（2）类型异质性检验显示,科技创新在成长型、成熟型城市中发挥了正向中介效应,在再生型城市中表现为间接抑制作用;外商直接投资在衰退型城市中的中介效应值为正,而在再生型城市中表现为负向中介效应;产业结构优化在成长型与成熟型城市中发挥了正向中介效应。（3）对比中介效应结果表明,全样本回归时,产业结构优化、外商直接投资和科技创新的中介效应梯次递减,产业结构优化的中介效应占比接近80%,环境规制的...     

气溶胶辐射效应对气象和环境影响的观测与模拟研究

选取2015年和2019年不同代表年份,结合外场观测和数值模拟,分析了天津地区不同季节不同天气(晴天、多云、霾)下,气溶胶辐射效应对整层大气透过率和地表入射太阳辐射的影响,以及这种影响在不同年份的差异.借助WRF-Chem模式模拟分析了重污染期间气溶胶辐射效应对垂直方向上气象要素廓线、边界层结构以及PM_2.5浓度的反馈机制.结果表明:霾污染可导致大气透过率明显下降,春、秋、冬不同季节,霾污染导致中午大气透过率分别下降0.09,0.11和0.09.全年平均霾污染可导致大气透过率降低约15.5%.云量的增多也可导致大气透过率明显下降,多云天气下大气透过率相比晴天减小约22.4%.霾和云对大气透过率的影响还与太阳高度角有关,当太阳高度角>60°时,霾污染导致大气透过率下降8.6%.随污染等级提高,气溶胶对太阳辐射的衰减作用也越强,天津地区空气质量分别为Ⅰ～Ⅰ级时,中午地表入射短波辐射呈稳定下降趋势,依次为484,446,439,342,328和253W/m².重污染期间,气溶胶辐射效应导致大气低层(250m以下)降温(0.8℃)增湿(3.8%...