国家重点生态功能区县域环境监测质量评价方法及应用示范

以国家重点生态功能区县域环境监测质量评价为目标,综合应用德尔菲法、层次分析法和模糊综合评价法,构建了国家重点生态功能区县域环境监测质量评价方法,并确定了评价因子、权重系数、计算方法。该方法评价指标共分为三层:第一层为目标层,即国家重点生态功能区县域环境监测质量;第二层为准则层,包括人员及资质、现场监测、实验室管理、报告编制及数据上报;第三层为方案层,包括人员操作、持证上岗、资质认定、人员培训、水质布点采样流转情况、空气自动站运维情况、现场质控实施情况、实验室环境条件、样品试剂的保存与管理、仪器检定与校准、实验室质量控制实施情况、数据填报软件运行情况、监测报告规范性等13个评价要素。经矩阵一致性检验确定了各评价要素的权重,将该权重与各要素得分运算后得到县域环境监测质量评价结果。在此基础上,选取广东、山西、陕西、四川和青海等5个省份的15个国家重点生态功能区县域作为典型区开展了实地调研,并应用评价体系对其进行了监测质量等级评价。结果表明,15个典型县域中,环境监测质量等级为优的县域占13.3%,一般、较差的县域分别占66.7%、20%。县域环境监测承担单位在资质、报告编制及数据上报方面表现较好,在现场监测、人员操作方面问题突出,在实验室管理方面有待提升。     

官厅水库入库断面水质多指标评价与演变特征分析

水体质量状况及其污染特征是流域水污染防治规划和治理措施制定的前提和基础。采用主成分分析和层次聚类分析等多元统计分析方法,选取溶解氧、高锰酸盐指数、化学需氧量等10个不同类型的监测指标,综合评价了官厅水库入库断面八号桥2006—2017年丰水期和枯水期水质年际变化特征,识别了不同阶段关键污染指标。结果表明:各年份丰水期(9月)大多数水质指标均优于枯水期(5月),特别是粪大肠菌群和氨氮,但总磷和高锰酸盐指数的差异较小。根据水质指标年际变化情况,可将研究期分为污染严重阶段(2006—2007年)、污染改善阶段(2008—2015年)和污染全面好转阶段(2016—2017年)。大部分水质指标呈现逐年好转的趋势,特别是粪大肠菌群、氨氮和五日生化需氧量,但总磷仍是官厅水库入库河流的重要污染指标。     

环境空气质量自动监测站的管理与维护

随着工业化、城镇化的深入推进,二氧化硫、氮氧化物、烟粉尘和挥发性有机物等各类污染物排放到环境中,致使中国大气受到严重污染,给人体的健康、动植物的生长、发育和繁殖等带来负面的影响。为实时监测环境空气质量,建立环境空气质量自动监测站逐渐成为大气污染防治的主要手段。文中以环境空气质量自动监测站为研究对象,提出环境空气质量自动监测站管理与维护面临的问题,探讨相应的解决措施,以期为环境空气质量自动监测站的管理与维护提供参考依据。     

快速城市化背景下的思雅河流域水环境分析

通过对思雅河流域连续3年的水环境质量监测,结合遥感影像获得其土地利用类型变化,据此研究城市化对水环境的影响。结果表明:2012—2014年间思雅河流域自然、农业景观面积占比减少,而建设用地面积持续增加;研究期间除TDS年均值略微下降外,其余水质指标的年均值几乎均呈递增趋势,尤以TSS和COD增加最显著;TSS、COD、NH 3-N和TP的相对标准偏差均>0.1,显著高于其余参数,说明其波动程度较大。主成分分析表明水环境变化最主要的影响因子为第一主成分(TSS、COD、NH 3-N和TP)。贵安新区大学城建设活动加重了思雅河流域水体污染趋势。     

便携式GC-MS仪快速测定水中硝基苯及其在应急监测中的应用

采用便携式GC-MS仪快速测定水中硝基苯,通过优化水中离子强度和顶空加热时间,使方法在0μg/L^300μg/L范围内线性良好,方法检出限为2.5μg/L。标准溶液6次测定结果的RSD为7.8%~10.9%,实际水样的加标回收率为80.7%~103%。同步测定试验表明,硝基苯与7种苯系物分离良好。与国标方法对比,该方法单个样品测定时间由2 h缩短为15 min。将该方法用于应急监测工作中,及时有效的数据可为污水处理及事故调查提供分析和研判依据。     

整合消费与增加值视角的中国行业碳排放变动分解研究

在研究影响我国CO 2排放因素领域,基于投入产出技术的分解模型已成为主要的分析工具,现有研究多分别基于消费视角或收益视角展开分析。为全面评估各行业收益与消费对其上游、下游行业碳排放的综合影响,整合基于收益与基于消费两个视角,运用2012年与2015年我国投入产出表,构建两层嵌套式结构分解分析模型(SDA),比较分析消费规模效应、收益规模效应、行业流入、流出增加值变动效应、增加值结构变动效应等14个影响各行业碳排放变动的关键因素,并借助对消费者原则碳排放估算公式的重构,更准确地实现从增加值视角对各行业消费者原则碳排放变动的关键影响因素分析。研究发现:①研究期内,我国在总产出增长29.14%的同时碳排放量上升1.46%,各行业碳排放强度下降是主要的减排因素,其中建筑业减排贡献最大。②增排效应方面,影响从大到小依次为消费规模、收益规模、完全投入结构与完全消费结构四项效应,且前两个规模效应的影响是后两个结构效应的2倍以上,尤其建筑业消费规模效应、煤炭采选产品业收益规模效应增排较大。③消费规模扩大导致增排的原因并非行业本身生产规模扩大,而主要在于建筑业、服务业等行业规模扩张时吸收其他行业流入的增加值量增多。④收益规模扩大导致的增排效应方面,细分来说从大到小依次为劳动者报酬、生产税净额、固定资产折旧、营业盈余四项效应,且行业差异显著,如煤炭采选产品业的劳动者报酬效应,石油、炼焦产品和核燃料加工品业的生产税净额效应以及电力、热力生产和供应业的营业盈余效应增排贡献较大,而煤炭采选产品业的营业盈余效应、批发、零售业和住宿、餐饮业的生产税净额效应则减排贡献较大。     

Point Sampling Digital Imagery with ‘Samplepoint’

Measuring percent occurrence of objects from digital images can save time and expense relative to conventional field measurements. However, the accuracy of image analysis had, until now, not reached the level of the best conventional field measurements. Additionally, most image-analysis software programs require advanced user training to successfully analyze images. Here we present a new software program, ‘SamplePoint,’ that provides the user a single-pixel sample point and the ability to view and identify the pixel context. We found SamplePoint to allow accuracy comparable with the most accurate field-methods for ground-cover measurements. Expert use of the program requires minimal training and its ease of use allows rapid measurements from image data. We recommend SamplePoint for calibrating the threshold-detection level of image-analysis software or for making direct measurements of percent occurrence from digital images.     

Monitoring of a Coastal Mediterranean Area: Culturable Bacteria, Phytoplankton, Environmental Factors and their Relationships in the Southern Adriatic Sea

Culturable heterotrophic bacterial and phytoplanktonic densities were investigated at four sites in the Southern Adriatic Sea (Brindisi, S. Cataldo, Otranto and S. M. di Leuca) over an annual cycle. The main phytoplankton groups, the bacterial biodiversity, as well as the faecal contamination indicators were determined. Culturable bacterial numbers averaged 4.8 ± 0.2 log CFU ml⁻¹ whereas phytoplankton numbers averaged 2.1 ± 0.4 log cells ml⁻¹. Relationships between culturable bacteria, phytoplankton and the environmental factors were established. Bacterial and phytoplankton densities usually depended significantly on temperature, dissolved oxygen, phosphate and nitrite only in the S. Cataldo transect. In all the examined transects phytoplankton showed a bloom during the January–February period followed by a bacterial peak during the February–March period. Thus we can suppose that the phytoplankton winter bloom is responsible for the availabily of organic matter for bacterial populations in the following months in this oligotrophic ecosystem.     

Assessing Impact of Urbanization on River Water Quality In The Pearl River Delta Economic Zone, China

The Pearl River Delta Economic Zone is one of the most developed regions in China. It has been undergoing a rapid urbanization since the reformation and opening of China in 1978. This process plays a significant impact on the urban environment, particularly river water quality. The main goal of this present study is to assess the impact of urban activities especially urbanization on river water quality for the study area. Some Landsat TM images from 2000 were used to map the areas for different pollution levels of urban river sections for the study area. In addition, an improved equalized synthetic pollution index method was utilized to assess the field analytical results. The results indicate that there is a positive correlation between the rapidity of urbanization and the pollution levels of urban river water. Compared to the rural river water, urban river water was polluted more seriously. During the urban development process, urbanization and urban activities had a significant negative impact on the river water quality.     

Qualidex – A New Software for Generating Water Quality Indice

Water quality indice are necessary for resolving lengthy, multi-parameter, water analysis reports into single digit scores. This, in turn, is essential for comparing the water quality of different sources and in monitoring the changes in the water quality of a given source as a function of time and other influencing factors.In this paper we present the computer-automated tool QUALIDEX (water QUALIty inDEX), which has been developed by us to generate and operate water quality indice. Several popular indice – such as the Oregon Water Quality Index developed in the 1970s by Oregon Department of Environmental Quality and later updated in 1995, the Aquatic Toxicity Index developed by Wepener and coworkers for protection of aquatic life at the Olifants river, Kruger National Park, South Africa, the water quality index developed by Dinius in 1987, the Overall Index of Pollution (of surface waters) developed at the National Environmental Engineering Research Institute (NEERI), and the water quality index of the Central Pollution Control Board (CPCB) – have also been added to QUALIDEX in modular form. There is also a New water quality index sub-module which enables the user to generate his or her own index and compare its performance with these well-known indice. The package is also capable of analyzing the variations in the water quality of different sites at different times. The software has been coded in Visual C++ and has been integrated with MS Access database.