中国城乡贫困变动:2004—2012

本文基于2004—2012年中国综合社会调查数据,根据家庭人均年收入2 300元的国家贫困标准线和"1天1.5美元"的亚洲贫困标准线,使用FGT指数和脱贫时间两种贫困指数评估了我国城乡贫困整体变动趋势,并从城乡和地区、个体和家庭特征层面分解贫困人口构成;也考察了贫困变动的增长效应和收入分配效应;最后定量地分析收入增长的影响因素。结果表明,根据两种贫困标准线,两种贫困指数测度结果一致反映我国贫困人口规模显著减少;按国家贫困标准线,我国城乡贫困发生率下降了8.8%,但到2012年的依然高达8.6%,农村贫困人口平均脱贫时间为5.4年,而相对贫困发生率有所上升。不同地区的贫困变动差异较大,西部地区和中部地区贫困发生率依然高于全国平均水平3.41个百分点和0.22个百分点,贫困强度和贫困深度现象都还较为严重;东部地区的减贫效应十分明显,但贫困人口内部收入差距拉大问题较为突出。经济增长的脱贫效应较为显著,但增长的亲贫性有待提高;城乡、地区和贫困人口内部居民收入差距逐渐拉大,并成为反贫困的严重障碍。外出非农工作经历、性别差异和教育程度是影响收入增长的关键因素。基于此,本文建议反贫政策应瞄准西部地区的教育程度和健康水平较低、家庭规模较大的农村居民,尤其是女性户主家庭,也应加强养老保险、社会帮扶和人力资本投资,形成改善收入分配为重点的社会保障性扶贫政策体系;中部地区可以借助邻近东部地区的地理优势,通过承接产业转移持续实施"开发式扶贫"政策体系;同时,也可将扶贫标准线提高为每人"1天1.5美元"的亚洲贫困线。     

Assessing coastal vulnerability to climate change: comparing segmentation at global and regional scales

Recent concerns about potential climate-change effects on coastal systems require the application of vulnerability assessment tools in order to define suitable adaptation strategies and improve coastal zone management effectiveness. In fact, while various research efforts were devoted to evaluate coastal vulnerability to climate change on a national to global level, fewer applications were carried out so far to develop more comprehensive and site-specific vulnerability assessments suitable to plan possible adaptation measures at the regional scale. In this respect, specific indicators are needed to address climate-change-related issues for coastal zones and to identify vulnerable areas at the regional level. Two sets of coastal vulnerability indicators were selected, one for regional and one for global studies, respectively, concerning the same features of coastal systems, including topography and slope, geomorphological characteristics, presence and distribution of wetlands and vegetation cover, density of coastal population and number of coastal inhabitants. The proposed set of indicators for the regional scale was chosen taking into account the availability of environmental and territorial data for the whole coastal area of the Veneto region and was based on site-specific datasets characterized by a spatial resolution appropriate for a regional analysis. Moreover, a GIS-based segmentation procedure was applied to divide the coastline into linear segments, homogeneous in terms of vulnerability to climate change and sea-level rise at the regional scale. This approach allowed to divide the Veneto shoreline into 140 segments with an average length of about 1 km, while the global scale approach identified four coastal segments with an average length of about 66 km. The performed comparison indicated how the more detailed approach adopted at the regional scale is essential to understand and manage the complexities of the specific study area. In fact, the 25-m DEM employed at the regional scale provided a more accurate differentiation of the coastal area's elevation and thus of coastal susceptibility to the inundation risks, compared to the 1-km DEM used at the global level. Moreover, at the regional level the use of a 1:20,000 geomorphological map allowed to differentiate the unique landform class detected at the global level (e.g., fluvial plain) in a variety of more detailed coastal typologies (e.g., open coast eroding sandy shores backed by bedrock) characterized by a different sensitivity to climate change and sea-level rise. Accordingly, the information provided by regional indicators can support decision-makers in improving the management of coastal resources by considering the potential impacts of climate change and in the definition of appropriate actions to reduce inundation risks, to avoid the potential loss of valuable wetlands and vegetation and to plan the nourishment of sandy beaches subject to erosion processes.     

An Overview of EPA's Regional Vulnerability Assessment (ReVA) Program

Regional Vulnerability Assessment (ReVA) is an approach to place-based ecological risk assessment that is currently under development by EPA's Office of Research and Development. The pilot assessment will be done for the mid-Atlantic region and builds on data collected for the Environmental Monitoring and Assessment Program. ReVA is being developed to identify those ecosystems most vulnerable to being lost or degraded in the next 5 to 50 years and to elucidate which stressors cause the greatest risk to ecosystem goods and services. The goal here is not exact predictions, but an early warning system to identify and prioritize the undesirable environmental changes we should expect over the next few decades. As such, ReVA represents a new risk paradigm for EPA that will require innovative approaches to combine existing knowledge, focus new research, and synthesize many types of information into a meaningful assessment designed to inform environmental decision-makers about future environmental risk.     

基于遥感的区域人居环境指数构建及其应用

基于生态宜居和以人为本双重理念,选取区域绿度、区域热度、区域蓝度、区域亮度、区域透明度和区域起伏度等6个指标,利用主成分分析法构建基于遥感的区域人居环境指数(RHEI).以福建省为例,分季度测算其RHEI,揭示区域人居环境的时空差异.结果表明:福建省RHEI随着季节变化逐渐降低,呈现东南低西北高、沿海岸线向内陆上升的空间分布格局.通过比较各指标的回归模型系数,发现区域蓝度对区域人居环境的影响最大,区域透明度的影响最小.由年度均值回归模型预测,未来每增加0.166单位的区域蓝度或减少0.278单位的区域热度,能提升0.1单位的人居环境质量.     

云南土壤锰元素背景值及其特征初探

云南省土壤锰元素含量呈对数正态分布,背景值低于全国和重庆地区,接近我国南方部分土壤锰元素背景值。比较高的是石灰土、棕壤;比较低的是黄棕壤、砖红壤。云南土壤的水平地带和垂直地带锰元素背景值分布有着明显的变化规律,土壤中锰的总含量受成土母质母岩的影响尤为明显;由于成土母质母岩中含锰量不等,各成土母质母岩发育的土壤锰元素背景值也有较大差异;不同土类的锰元素背景值在同种母质母岩中也不相同;土壤锰元素背景值在滇西和滇西北地区较高,其余地区的土壤锰元素背景值呈无规律性的镶嵌分布。     

氯苯类化合物在大气中分布特征探究

建立环境空气和有组织废气排放模拟污染源,以玻璃纤维滤膜+玻璃棉和活性炭为吸附材料采集大气中氯苯类化合物,使用气相色谱法测定各组分,考察氯苯类化合物在大气气相和颗粒物中的分布特征。结果显示,环境空气和固定污染源有组织排放废气中一氯代至四氯代苯类各组分主要分布在大气气相中,颗粒物中少有分布,说明现行环境监测方法以固体吸附剂采集测定大气中的氯苯类化合物可行。     

采煤沉陷区表层水及沉积物中微塑料的赋存特征

以淮南市采煤沉陷区为研究对象,分析表层水和沉积物中微塑料的分布特征、来源和风险。结果表明：研究区表层水中微塑料丰度为833个/m³～2 750个/m³,粒径以0.5 mm～1 mm为主,占比为33.53%,形状以纤维状为主,占比为72.17%,颜色以蓝色为主,占比为61.38%;沉积物中微塑料丰度为30个/kg～91个/kg,粒径以1 mm～2 mm为主,占比为32.19%,形状以纤维状为主,占比为89.99%,颜色以蓝色为主,占比为70.37%。研究区微塑料主要成分为聚对苯二甲酸乙二醇酯（37.23%）和聚酰胺（30.98%）,可能来源于纤维类生产、生活用品;沉陷湖泊微塑料的污染风险等级不高于Ⅱ级,风险较小。     

厦门市光化学污染特征分析

在2013年4月11日—5月22日期间测定厦门市过氧乙酰硝酸酯,研究该地区光化学污染过程,并统计移动源、植物、工业VOCs的排放量。结果表明,光化学污染不仅产生PM2.5,引起市区NO2浓度升高,还会加重霾的产生和污染水平,提出通过优化树种以降低光化学污染。     

Summer time haze characteristics of the urban atmosphere of Gwangju and the rural atmosphere of Anmyon, Korea

An extensive visibility monitoring was carried out simultaneously in the urban area of Gwangju and the rural area of Anmyon, Korea. This study examines patterns of visibility impairment and haze-forming pollutant concentrations on both sites resulting from natural and anthropogenic sources of gases and particles. Optical visibility measurements by a transmissometer, a nephelometer and an aethalometer provide aerosol light extinction, scattering, and absorption coefficients for both sites. In order to investigate the physico-chemical characteristics of atmospheric aerosols, aerosol samples were collected by various aerosol samplers at GJVMS (Gwangju Visibility Monitoring Station) and at KGAWO (Korea Global Atmosphere Watch Observatory), respectively. In addition, haze characteristics causing visibility impairment at those two sites were analyzed to obtain source contributions by regionally transported aerosols using grid analysis and display system (GrADS) from NECP reanalysis data. During the intensive monitoring period, ammonium sulfate was dominantly responsible for the fine particle mass loading at GJVMS, whereas organic carbon was the largest contributor at KGAWO. Light scattering by particles accounted for 52.8 to 81.3% of the range at the urban site, GJVMS and for 72.1 to 94.2% of the range at the rural site, KGAWO. Light absorption by the EC and NO₂ was between 14.5 and 34.8% at GJVMS, which was higher than the observed 1.1 ∼ 6.8% at KGAWO, respectively. Light scattering by aerosol was higher in the rural area than in the urban area. And organic carbon concentration was observed to be significantly higher than the concentration of elemental carbon at KGAWO. These haze-forming carbonaceous particles originate from anthropogenic pollutants at the urban atmosphere but they can be produced by natural environments such as marine and forest at the rural atmosphere.     

郑州市中心城区高铁锰地下水成因与分布规律

于2020年在郑州市中心城区布设273个监测点采集浅层地下水样品,分析地下水中铁和锰的空间分布特征.结果表明,研究区浅层地下水出现高铁锰现象的原因为区内第四纪中更新统和上更新统沉积物中铁锰质结核及浸染经淋溶进入地下水;浅层地下水中铁和锰含量具有伴生关系,铁锰超标区域相对集中,高铁锰区主要分布在黄河南岸局部地区;该区域浅层地下水为还原环境,有利于铁和锰的富集,pH值大多在7.1～8.0范围内,呈弱碱性,沿地下水径流方向,铁和锰含量随硝酸盐含量增加而降低,随硫酸盐和氯化物含量增加而增加.