基于模糊逻辑的北京城市边缘区土壤重金属污染空间预测

Fuzzy classification combined with spatial prediction was used to assess the state of soil pollution in the peri-urban Beijing area. Total concentrations of As, Cr, Cd, Hg, and Pb were determined in 220 topsoil samples （0-20 cm） collected using a grid design in a study area of 2 600 kin2. Heavy metal concentrations were grouped into three classes according to the optimum number of classes and fuzziness exponent using the fuzzy comean （FCM） algorithm. Membership values were interpolated using ordinary kriging. The polluted soils of the study area induced by the measured heavy metals were concentrated in the northwest corner and eastern part, especially the southeastern part close to the urban zone, whereas the soils free of pollution were mainly distributed in the southwestern part. The soils with potential risk of heavy metal pollution were located in isolated spots mainly in the northern part and southeastern corner of the study region. The FCM algorithm combined with geostatistical techniques, as compared to conventional single geostatistical kriging methods, could produce a prediction with a quantitative uncertainty evaluation and higher reliability. Successful prediction of soil pollution achieved with FCM algorithm in this study indicated that fuzzy set theory had great potential for use in other areas of soil science.     

湿地土壤质量退化的模糊综合评价

Wetland soil quality degradation caused by large-scale agricultural reclamation on the Sanjiang Plain of Northeast China has been widely reported. A relative soil quality evaluation (RSQE) model and a projection pursuit evaluation (PPE) model based on real-coded accelerating genetic algorithm were introduced to evaluate quality variations in top layers of the main wetland soils on the Sanjiang Plain in 1999 and 2003, respectively. As soil quality degradation boundaries were vague, this study established two fuzzy synthetic evaluation (FSE) models based on the original data and criteria used in the RSQE and PPE models. The outputs of the two FSE models were obtained by choosing two fuzzy composite operators M (∧,∨) and M (?,⊕). Statistical analysis showed that the results of the FSE, RSQE, and PPE models were correlated. In particular, outputs of the FSE model using M (?,⊕) were significantly correlated with those of the RSQE model with r = 0.989 at P < 0.01. Compared with RSQE and PPE models, the FSE model may be more objective in showing soil quality variations and was closer to the natural situation, showing the feasibility and applicability of the FSE model in evaluating soil quality degradation. However, the choice of composite operator was of critical importance. The study of wetland soil quality degradation on the Sanjiang Plain was of scientific and practical significance for protection and management of soils and for sustainable development of agriculture in this area in the future.     

中国三种典型耕作土壤的农学土壤测试磷与环境学土壤测试磷的关系研究

A study was conducted to determine the relationships between agronomic soil test P and environmental soil test P in three soils predominately distributing in three typical agricultural production areas of China. Soil P was analyzed using Bray-1 （BP）, Olsen （OP）, and Mehlich-3 （MP） methods as agronomic tests, and using Fe-oxide impregnated filter paper （FeP）, anion-exchange resin membrane （RP）, and water （WP） as environmental tests. There were linear relationships between soil P extractable with all the tests evaluated. The regression coefficients, R^2, ranged from 0.8164 to 0.9409 between each two of the agronomic soil test P, and ranged from 0.4702 to 0.8990 between each two of the environmental soil test P, when the three soils were considered separately. When soil test P was analyzed across all the three soils, the highest regression R^2 was found between OP and MP （0.7940） amongst agronomic soil test P, and between FeP and RP amongst environmental soil test P （0.8842）. While all of the three agronomic soil test P was linearly related to each of the environmental soil test P across the three soils, strongest relationships were found between OP and environmental soil test P. Agronomic OP may be adopted as an analytical tool for environmental prediction of soil P.     

基于多元统计和模糊模型的沣河沉积物重金属污染风险评估

Concentrations of heavy metals in 74 sediment samples from the Fenghe River, which originates from the north of the Qinling Mountains and flows through Xi’an, Shaanxi Province, China, were characterized by employing geographic information system (GIS) mapping, fuzzy synthetic assessment, and multivariate statistical analysis to determine the enrichment characteristics of heavy metals as well as their potential risks of pollution to sediments. Al, Cd, and Co were the major pollutants, with a high enrichment factor (EF) value. Heavy metal concentrations from samples near the paper plant were maintained at a high level. Significant enrichment of Al, Ba, Cr, Ni, Pb, and Co was found in the midstream and downstream, while high concentration of Cu occurred in the headwater stream. Based on the cluster and principal component analyses, sediment metals mainly came from the paper plants, agronomic practices, natural sources, and tourism, with a contribution of 51.59%, 23.01%, 14.21%, and 9.88%, respectively. Sediment pollution assessment explored using fuzzy theory based on the entropy method and toxicity coefficient showed that 26, 32, and 11 sites fell into Class III (slightly polluted), Class IV (moderately polluted), and Class V (heavily polluted), respectively, and their scores of membership degree in the polluted level were on the rise, suggesting a relatively high degree of sediment metal pollution in the study area. Closely related to the excessive industrial and agricultural applications, metal pollution in sediment is necessary to be addressed in the Fenghe River.     

免疫算法在土壤资源质量评价中的应用

Based on the geographic information system （GIS） technology, ArcInfo software was adopted to collect, process and analyze spatial data of Guangdong Province for an evaluation of soil resource quality. The overlay analysis method was used in combining evaluation factors of Guangdong soil resource quality to determine the evaluation units. Because of its favorable convergent speed and its ability to search solutions, the immune algorithm was applied to the soil resource quality evaluation model. At the same time, the evaluation results of this newly proposed method were compared to two other methods： sum of index and fuzzy synthetic. The results indicated that the immune algorithm reflected the actual condition of soil resource quality more exactly.     

基于对象的方法(优于像素法)对巴西大西洋雨林地区的一个保护区进行土地覆盖分类

Conventional image classification based on pixels hinders the possibilities to obtain information contained in images, while modern object-based classification methods increase the acquisition of information about the object and the context in which it is inserted in the image. The objective of this study was to investigate the performance of different classification methods for land cover mapping in the vicinity of the Alto Ribeira Tourist State Park, a Brazilian Atlantic rainforest area. Two classification methods were tested, including i) a hybrid per-pixel classification using the image processing software ERDAS Imagine version 9.1 and ii) an object-based classification using the software eCognition version 5. In the first method, six different classes were established, while in the second method, another two classes were established in addition to the six classes in the first method. Accuracy assessment of the classification results presented showed that the object-based classification with a Kappa index value of 0.8687 outperformed the per-pixel classification with a Kappa index value of 0.2224. Application of the user’s knowledge during the object-based classification process achieved the desired quality; therefore, the use of inter-relationships between objects, superclasses, subclasses, and neighboring classes were critical to improving the efficiency of land cover classification.     

阳离子表面活性剂改性水稻土对甲磺隆和苄嘧磺隆的吸附

The distribution of light fraction carbon （LF-C） in the various size classes of aggregates and its relationship to water- stable aggregates as well as the influence of cultivation on the organic components in virgin and cultivated black soils were studied by wet sieving and density separation methods. The total organic carbon （TOC） and LF-C were significantly higher （P≤ 0.05） in the virgin soils than in the cultivated soils. The LF-C in aggregates of different size classes varied from 0.9 to 2.5 g kg^-1 in the cultivated soils and from 2.5 to 7.1 g kg^-1 in the virgin soils, whereas the ratio of LF-C to TOC varied from 1.9% to 7.3% and from 5.0% to 12.2%, respectively. After being incubated under constant temperature and controlled humidity for three months, the contribution of LF-C to TOC sharply decreased to an amount （1.7%4.5%） close to the level in soils that had been cultivated for 20 to 25 years （1.3%-8.8%）. As a result, the larger water-stable macro-aggregates （especially 〉 1 mm） decreased sharply, indicating that the LF-C pool in virgin soils declined quickly after cultivation, which reduced the water stability of soil aggregates.     

华北平原土壤质量与农业生产的关系

Sustainable agricultural production is of vital importance to food supply security. This study aimed to investigate crop yield response to spatial variability of soil quality at a county scale in the North China Plain(NCP) and subsequently derive key soil quality indicators. Soil samples were geo-referenced and taken in 2008 from both surface(0–20 cm) and subsurface(20–40 cm) layers in132 fields throughout the Fengqiu County, located in the centre of the NCP, for subsequent soil properties' analyses. Annual crop yields were obtained from the same fields where soil samples were collected. Soil quality was evaluated based on a fuzzy set with 13 soil properties, and its spatial distributions were investigated by integrating geostatistical analysis and geographic information system(GIS) techniques. Soil quality indices were classified into five grades, and their spatial distributions were mapped within the county.The surface soil qualities were about one to two grades higher than the subsurface soil. The quality indices for surface and subsurface soils were positively associated with the annual crop yields, suggesting the importance of both. Soil organic matter, total nitrogen,available P, and available K contributed 50% of the combined weight to the soil quality index and were identified as key indicators of soil quality status in the area in terms of sustainability.     

磷矿粉在酸性土壤中的施用: 比较磷酸盐提取方法测定磷矿粉溶解程度

Three phosphate extraction methods were used to investigate the dissolution,availability and transfo-mation of Kunyang phosphate rock(KPR) in two surface acid soils.Dissolution was determined by measuring the increase in the amounts of soluble and adsorbed inorganic phosphate fractions,and did not differ signifi-cantly among the three methods.Significant correlations were obtained among P fractions got by the three extraction methods.Dissolution continued until the end of the 90-day incubation period.At the end of the period,much of the applied phosphate recovered in both soils were in the Al- and Fe-P or in the hydroxide-and bicarbonate-extractable inorganic P fractions.The dissolution of KPR in the two soils was also similar: increased addition of phosphate rock resulted in decreased dissolution.The similarity in the order and extent of dissolution in the two soils was probably due to the similarity in each soil of several factors that are known to influence phosphate rock dissolution,namely low CEC,pH,P level,and base status;and high clay and free iron and aluminum oxide contents.The results suggested that KPR could be an aternative P source in the soils are not limiting.     

基于GIS技术的红壤资源划分与评估

A small scale red soil resources information system(RSRIS) with applied mathematical models was developed and applied in red soil resources(RSR) classification and evaluation,taking Zhejiang Province,a typical distribution area of red soil,as the study area.Computer-aided overlay was conductied to classifty RSR types.The evaluation was carried out by using three methods,i.e.,index summation,square root of index multiplication and fuzzy comprehensive assessment,with almost identical results,The result of index summation could represent the basic qualitatie condition of RSR,that of square root of index miltiplication reflected the real condition of RSR qualitative rank,while fuzzy comprehensive assessment could satisfactorily handle the relationship between the evaluation factors and the qualitative rank of RSR,and therefore it is a feasible method for RSR evaluation.     

洛川苹果园地土壤重金属污染调查与评价

通过对洛川苹果园地土壤样品的采集、监测,依据无公害果园产地土壤环境质量标准和绿色食品产地土壤环境质量标准,重点分析评价了对土壤环境及人体危害较大的Cd、As、Cr、Pb等重金属元素的污染现状。评价结果表明:以无公害果园产地土壤环境质量为评价标准,洛川苹果园地土壤重金属污染程度有As>Cr>Cd>Pb的特征,土壤重金属综合污染指数为0.51,土壤Cd、As、Cr、Pb单项污染指数平均值均小于0.7,土壤环境中的重金属元素含量现状水平符合无公害苹果生产的要求;以绿色食品产地土壤环境质量为评价标准,洛川苹果园地土壤重金属污染程度有As>Pb>Cr>Cd的特征,土壤重金属综合污染指数为0.64,土壤Cd、Cr、Pb单项污染指数平均值均小于0.7,土壤As单项污染指数平均值大于0.7,但小于1。土壤环境中的重金属含量现状水平符合绿色食品苹果生产的要求。但土壤As单项污染指数平均值为0.74,已超过绿色食品产地土壤污染警戒线。洛川苹果园地土壤重金属As污染程度较高,主要是由于人为长期不合理使用含As农药、化肥所致。因而,洛川苹果生产中应将土壤环境中的As作为严控的土壤污染物。     

太原市污灌区土壤重金属污染现状评价

对太原市污灌区土壤重金属分布特征进行了分析评价,结果表明重金属Pb、Zn、Cu、Ni、Mn、Cr、As、Hg、Cd含量均值均未超过土壤环境质量标准（GB15618—1995）,但其平均值均显著高于太原市土壤背景值。各重金属间的相关分析表明,Pb、Zn、Cu、Ni、Mn、Cr、As、Cd之间呈极显著相关,说明这8种元素污染源可能相同。Hg是本区表层土壤重金属污染的主要因子,重金属元素的污染程度依次为Hg〉Cd〉Pb〉As〉Cu〉Zn〉Cr〉Mn〉Ni。土壤重金属单项污染指数均值均大于1,综合污染指数为2.81,总体上,污染水平为中度及其以上。各种重金属单因子污染指数和综合指数在研究区有相似的空间分布格局,总体分布趋势为东南部小店地区和中南部晋源区相对较高,南部清徐县相对较小;通过因子分析并结合污灌区污染源调查,表明Hg除受污水灌溉的影响外,燃煤释放的Hg可能是重要来源之一,Cd、Zn、Pb和Cu可能来自污水灌溉和大气沉降,以污水灌溉的贡献为主,Ni、Mn、As、Cr来自污水灌溉。Hg、Cd是太原市污灌区土壤中需要优先控制的重金属。     

苏南某市农田土壤环境质量评价及其分级

以苏南工业化与城市化水平较高的某市为试验区,在对该市农田土壤环境质量和污染状况进行较为系统的调研之后,对试区农田土壤的环境质量按照国家有关标准进行综合评价并分类。结果表明:单因子污染指数最小的是六六六,其次为Pb和Cr,均无超标样点;少数传统菜地和大棚菜地土壤中DDT的污染指数接近或超过1,表明其中DDT残留量已超标,单因子污染指数最为严重的是Cd。就综合污染指数而言,除水稻土均值为0.57,低于0.7,属安全外,其他3类土壤的综合污染指数均值在0.72~0.95之间,处于警戒值。试区内约有20%以上土壤综合污染指数超过1,表明土壤受到轻度污染,这是需要引起关注的。     

基于GIS的杭州市居民区土壤重金属污染现状及空间分异研究

研究了杭州市50个代表性居民小区土壤重金属(Cd、Cr、Cu、Ni、Pb和Zn)的含量,按照国家《土壤环境质量标准》对该市居民区土壤重金属污染状况做出了评价,并在GIS技术支持下,研究了土壤重金属污染的空间变异性。结果表明,杭州市居民区土壤均受到了不同程度的污染。其中4%的土壤轻度污染,54%的土壤中度污染,42%的土壤严重污染。土壤重金属污染具有显著的空间分异特征,严重污染区域大致呈西北-东南走向,包括了城北的大部分地区、市中心和城东南一些地区。工业生产和居民区形成时间对居民区土壤重金属积累有较大的影响。     

葫芦岛锌厂周围土壤镉污染现状研究

本文对葫芦岛锌厂周围土壤中重金属镉含量进行了分析检测,并用三种评价标准(当地土壤背景值、土壤污染起始值和土壤环境质量标准)分别对土壤镉的污染程度进行了评价,结果表明:锌厂周围土壤受镉污染严重。三种评价方法均表明锌厂南部和西部5km、北部10km范围内的表层土壤(0～20cm)达到了重度污染、北部15km处为中度-重度污染、北部20km处受到轻度污染。锌厂南部土壤镉的含量最高,其次是北部的土壤,含镉量分别超过土壤环境质量标准的19.23～109.23倍和4.13～11.63倍;而西部土壤镉含量相对较低。下层土壤(20～40cm)也受到了不同程度的污染,大部分剖面点达到了中度到重度的污染。在所研究范围内土壤上下层含镉量比值为1.3～17.9。     

辽宁省污灌区土壤重金属污染特征与生态风险评价

针对当前污灌区土壤污染研究中存在的问题,提出了一种模糊识别模型评价土壤综合环境质量,并对潜在生态风险指数法进行改进,用以计量重金属潜在生态风险。采用建立的方法对辽宁省污灌区土壤环境质量和重金属潜在生态风险进行了评价,结果显示:Cd是辽宁省污灌区首要重金属污染物,而Hg、Pb、Ni污染较为普遍;重金属的来源主要是灌溉污水和农田施肥;以工业废水为灌溉用水的灌区污染情况比以河水为灌溉用水的灌区污染严重;污灌区重金属元素污染程度大小依次为:Cd>Pb>Ni>Hg>Cu>Cr>As,而重金属潜在生态风险从大到小则依次为:Cd>Hg>Pb>Cu>Ni>As>Cr。总体来看,辽宁省污灌区存在一定程度的重金属污染,且具有较为明显的复合型污染特点,其潜在生态风险超出警戒水平,各灌区应根据各自污染特点和风险等级制定相应的污染防治对策。     

冶炼厂周边土壤重金属污染范围的界定与不确定性分析

在浙江省富阳市某冶炼厂周边以网格法采集了147个表层土壤样品,测定了铜、锌、铅和镉总含量。运用组合预测法(普通块状克里格法和三角网格插值法)预测了研究区各种重金属含量的空间分布,又运用指示克里格法预测了研究区各种重金属的污染概率;再分别依据土壤污染临界值(土壤环境质量标准)和污染概率的临界值(50%)来界定各种重金属的污染范围。本研究将基于两种方法的界定结果相对比来综合界定污染范围,并将污染土壤重金属污染状况分为污染、未污染和不确定。综合界定结果表明,研究区分别有71.7%、80.0%、3.0%、83.1%的区域土壤被重金属Cu、Zn、Pb、Cd所污染,不能被确定是否被重金属Cu、Zn、Pb、Cd所污染的区域分别占20.8%、10.5%、12.5%和10.9%。     

改进灰色模式识别模型评价洱海雨季灌排沟渠水质

为揭示洱海流域农田生产与农村生活单元交替分布对灌排沟渠水质的综合影响及污染物贡献率,选取流域典型灌排沟渠不同断面进行连续取样观测,在分析化学需氧量(chemical oxygen demand,COD)、总氮(total nitrogen,TN)、总磷(total phosphorus,TP)及铵态氮(ammonium nitrogen,NH_4~+-N)浓度变化特征基础上,采用"中心化"灰色模式识别模型和综合平均污染指数对沟渠农田入口-农田出口-村落出口-农田出口-村落出口-农田出口断面水质进行综合评价。结果表明:沟渠断面TP和总可溶磷(totaldissolved phosphate,TDP)浓度沿水流方向持续增加,TN和硝态氮(nitrate nitrogen,NO_3~--N)浓度先增加随后稳定,沟渠农田出口段NH_4~+-N和COD浓度分别削减13.43%～57.88%和2.88%～19.33%,而流经村落段浓度相应增加。灰色模式识别模型分析发现沿水流方向沟渠断面水质类别分别为Ⅲ类、Ⅱ类、Ⅳ类、Ⅳ类、Ⅴ类和Ⅴ类,综合平均污染指数法表明沟渠中TN和COD是水体主要污染因子,而NO3--N是水体TN的最主要形态。该研究可揭示洱海流域氮磷污染来源与贡献,为明确面源污染防治的主要污染因子提供科技支撑。