Impact of socioeconomic development on ecosystem services and its conservation strategies: a case study of Shandong Province,China

Ecosystems and their components provide a lot of benefits for the welfare of human beings. Coupled with increasing socioeconomic development, most of the rapidly developing and transitional countries and regions have been experiencing dramatic land use changes. This has resulted in a large amount of forestland, grassland, and wetland being occupied as residential and industrial land or reclaimed for arable land, which in turn results in a sharp deterioration of ecosystem services around the world. Shandong Province, an economically powerful province of China, was chosen as a case study in order to capture the impact of socioeconomic development on ecosystem services. By way of the study, land uses and their changes were categorized between 1980 and 2006, and the ecosystem services capital and changes of 111 counties of Shandong Province in different phases were evaluated, as well as the total ecosystem services capital, followed by the zoning of ecosystem services function region of Shandong Province. We found that the counties in mountainous areas and wetlands, where generally the prefectural-level cities are located with a rapid socioeconomic development, experienced a successive deterioration of ecosystem services especially during the 2000s. Finally, three conservation strategies for managing and improving ecosystem services were proposed and discussed with the aim of achieving coordinate and sustainable development of the socioeconomy, environment, and ecosystems not only in Shandong Province but also in other provinces of China, as well as in other developing and transitional countries and regions.     

Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China

Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl^?), calcium (Ca²⁺), total alkalinity, total hardness, nitrate nitrogen (NO₃-N), and ammonical nitrogen (NH₄-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO₃-N, NH₄-N, and Ca²⁺. Cl^? was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters.     

Determination of hydrazine hydrate based on electrochemiluminescence of Ru(bpy) 3 2+

Considering of the basic properties and also the two nitrogen atoms in the structure, hydrazine hydrate was employed to be an amine additive candidate, to build a Ru(bpy) ₃ ²⁺ /hydrazine electrochemiluminescence (ECL) system, and ECL of Ru(bpy) ₃ ²⁺ has been employed for the determination of hydrazine hydrate in the paper. The result demonstrated that the logarithmic ECL increasing (ΔECL?=?ECL_{after addition of hydrazine}???ECL_{before addition of hydrazine}) versus the logarithmic concentration of hydrazine hydrate is linear over a concentration range of 1.0?×?10^?9 to 1.0?×?10^?5?mol/L, on both glassy carbon and Pt electrodes in a pH 9 phosphate buffer. The hydrazine hydrate detection limit was down to 1.0?×?10^?9?mol/L, comparatively lower than other detection methods. To check its applicability, the proposed method was applied to the determination of hydrazine hydrate added into a tap water sample with good reproducibility and stability. All these provide a possibility to develop a novel ECL detection method for hydrazine in water.     

基于顺序注射分析技术的总氮在线分析仪

针对环境监测领域,研制了一种基于顺序注射分析技术的总氮在线分析仪。该分析仪以注射泵为分析过程的液体驱动定量单元,以多通道选向阀为流路切换单元,以发光二极管和硅光电管为检测单元。在该分析平台上,含氮化合物在高温高压条件下经过硫酸钾氧化成硝酸根,硝酸根被还原为亚硝酸根后与N-(1-萘基)乙二胺盐酸盐生成偶氮染料,再由光电检测单元测定吸光度值,经计算得到总氮含量。与现有的总氮在线分析技术相比,该分析仪具有检测单元简单、生产成本低、测量精度高、试剂消耗和废液产生量少等优点,适合于环境监测等领域的长时间在线分析。     

测定环境空气中砷及其化合物的方法改进

对《空气和废气监测分析方法》中砷的采样和测定方法进行了改进,并在云南某炼铜厂环境空气中含砷监测进行了实际验证。结果表明,方法的检出限、精密度、准确度均能满足测定的要求,并且更适合测定高浓度砷。     

西安市黑碳气溶胶浓度特征及与气象因素和常规污染物相关性

利用西安市环境监测站超级站2013年9月1日—2015年5月31日黑碳气溶胶(BC)的监测数据,研究空气中BC浓度特征及其与气象因素和常规污染物相关性。结果表明:BC小时平均浓度均值在春季、夏季和冬季的变化趋势呈"W"型,秋季呈"V"型,且冬季的第一个最低值和峰值比春季和夏季的分别延迟1 h和2~3 h,且20:00~次日6:00秋季BC小时平均浓度均值高于当年冬季。BC浓度在秋季和冬季较高,夏季较低。冬季BC/PM_(2.5)基本最低,秋季BC/PM_(2.5)相对最高。BC日平均浓度与气温、降水和风速的日平均值为极负显著相关,且风速小于1.0 m/s时,其与风速呈最显著的负相关。除O_3外,BC日平均浓度与其他常规空气污染物浓度呈显著相关,表明其同源性很强,且受机动车尾气排放的影响更大。     

基于环境一号卫星的PM2.5浓度遥感反演研究

2014年12月29—30日,青岛市发生了一次空气污染过程,利用环境一号卫星CCD遥感影像数据和实测PM_(2.5)浓度数据,分析了该过程前后5 d的实测PM_(2.5)浓度与环境一号卫星CCD遥感影像的DN值之间的相关性,分别按日期和区域建立了反演模型。结果表明,按日期拟合反演模型相关系数为0.02~0.51,按区域拟合反演模型相关系数为0.01~0.80,总体来说,区域拟合结果较好。     

碱片-离子色谱法测定硫酸盐化速率影响因素

采用碱片-离子色谱法测定空气的硫酸盐化速率,方法在硫酸盐质量浓度为1.00~20.0 mg/L范围内线性良好(r≥0.999 0);碱片剪碎或不剪碎对空白碱片中硫酸根离子质量浓度的测定无明显影响,且高低两种加标浓度的回收率均在80.0%~120%之间;对于碱片实际样品,碱片剪碎更有利于硫酸根离子的快速溶出;随浸泡时间的延长,碱片中溶出的硫酸根离子质量浓度呈上升趋势,7 h硫酸根离子基本溶出完全,从保证结果质量和节省时间的角度考虑,确定最佳浸泡时间为3.5 h,建议碱片全部采取剪碎处理。     

环境监测市场化管理工作思考

阐述了我国及其他国家环境监测市场管理的经验,以及我国在推进环境监测市场化管理方面的探索;指出了目前环境监测市场化管理中存在的问题,提出,应加快建立适合国情的监测总体格局;建立完善环境监测社会化监管制度体系;充分发挥行业协会在监管中的作用;强化对社会监测机构监管力度;提高社会环境监测机构能力。