Linear alkylbenzenes in riverine runoff of the Pearl River Delta (China) and their application as anthropogenic molecular markers in coastal environments

The average concentrations of ∑LABs (sum of C₁₀-C₁₃-LABs) in runoff samples collected from the eight major riverine outlets of the Pearl River Delta (PRD) of China ranged from 1.4 to 6124 ng/L in the dissolved phase and from 0.01 to 11.4 μg/g dry weight in the particulate phase during March 2005-February 2006. The annual riverine flux of ∑LABs from the PRD to the coastal ocean was estimated at approximately 14 tons/yr. The inventories of ∑LABs in agricultural lands of Guangdong Province ranged from 313 to 1825 kg/yr. The early and late rice fields were the major sink of LABs, accounting for approximately 68% of total LABs inventory in agricultural lands. The social-economically estimated annual discharge of LABs from household detergents in the PRD was ∼696 tons/yr, more than an order of magnitude higher than that estimated from field measurements (about 14 tons/yr), which was attributed to several factors.     

Predictive Model for Motorcycle Accidents at Three-Legged Priority Junctions

In conjunction with a nationwide motorcycle safety program, the provision of exclusive motorcycle lanes has been implemented to overcome link-motorcycle accidents along trunk roads in Malaysia. However, not much work has been done to address accidents at junctions involving motorcycles. This article presents the development of predictive model for motorcycle accidents at three-legged major-minor priority junctions of urban roads in Malaysia. The generalized linear modeling technique was used to develop the model. The final model reveals that motorcycle accidents are proportional to the power of traffic flow. An increase in nonmotorcycle and motorcycle flows entering the junctions is associated with an increase in motorcycle accidents. Nonmotorcycle flow on major roads had the highest effect on the probability of motorcycle accidents. Approach speed, lane width, number of lanes, shoulder width, and land use were found to be significant in explaining motorcycle accidents at the three-legged major-minor priority junctions. These findings should enable traffic engineers to specifically design appropriate junction treatment criteria for nonexclusive motorcycle lane facilities.     

碳排放强度与能耗强度线性关系研究

碳排放强度与能耗强度是国家和地方2个重要的政策管控指标,二者存在潜在的逻辑关系,但就二者定量关系还存在分析不足,部分认识不统一的现象。通过建立碳排放强度同比变化率与能耗强度同比变化率之间关系的数学模型,分析能耗强度同比变化场景下碳排放强度同比变化趋势。对单位地区生产总值碳排放强度与单位地区生产总值能耗强度之间的线性关系进行了研究。结果表明,碳排放强度同比变化率与能耗强度同比变化率不是必然呈现“同正或同负”的关系,即能耗强度上升,碳排放强度也有可能下降;能耗强度下降,碳排放强度也有可能上升。研究为推动碳排放强度、能耗强度“双下降”的研究和决策提供参考。     

Monitoring of the Endangered Pinna nobilis Linné, 1758 in the Mar Grande of Taranto (Ionian Sea, Italy)

Two methods were used to calculate the meteorologically adjusted ground level ozone trends in southern Taiwan. The first method utilized is a robust linear regression method. The second approach uses a multilayer perceptron (MLP) artificial neural network (ANN) method. The observations obtained from 16 monitoring stations were analyzed and divided into six groups by hierarchical divisive clustering procedure. The daily maximum 1 and 8 h ozone concentrations for each group are then calculated. The meteorologically adjusted trends obtained by linear regression and MLP methods are smaller than the unadjusted trends for all groups and average time. It indicts that the meteorological conditions in Taiwan tend to increase ambient ozone concentrations in recent years.     

Assessment of risk to aquatic biota from elevated salinity -- a case study from the Hunter River, Australia

A linear engineering project--i.e. a pipeline--has a potential long- and short-term impact on the environment and on the inhabitants therein. We must find better, less expensive, and less time-consuming ways to obtain information on the environment and on any modifications resulting from anthropic activity. We need scientifically sound, rapid and affordable assessment and monitoring methods. Construction companies, industries and the regulating government organisms lack the resources needed to conduct long-term basic studies of the environment. Thus there is a need to make the necessary adjustments and improvements in the environmental data considered useful for this development project. More effective and less costly methods are generally needed. We characterized the landscape of the study area, situated in the center and north-east of Argentina. Little is known of the ecology of this region and substantial research is required in order to develop sustainable uses and, at the same time, to develop methods for reducing impacts, both primary and secondary, resulting from anthropic activity in this area. Furthermore, we made an assessment of the environmental impact of the planned linear project, applying an ad hoc impact index, and we analyzed the different alternatives for a corridor, each one of these involving different sections of the territory. Among the alternative corridors considered, this study locates the most suitable ones in accordance with a selection criterion based on different environmental and conservation aspects. We selected the corridor that we considered to be the most compatible--i.e. with the least potential environmental impact--for the possible construction and operation of the linear project. This information, along with suitable measures for mitigating possible impacts, should be the basis of an environmental management plan for the design process and location of the project. We pointed out the objectivity and efficiency of this methodological approach, along with the possibility of integrating the information in order to allow for the application thereof in this type of study.     

乡村转型发展影响因素及其作用效应的空间分异——以陕西省为例

以陕西省为例,围绕人口、土地、产业等乡村社会经济发展要素构建乡村转型发展评价指标体系,借助ArcGIS平台分析陕西省乡村转型发展时空格局演化特征;利用逐步回归、地理加权回归模型（GWR模型）对陕西省乡村转型发展影响因素及作用效应的空间分异进行探究,以期为陕西省乡村高质量发展路径设计与政策制订提供参考依据。研究结论如下：（1）2005—2017年间,陕西省乡村转型发展程度呈现持续上升趋势,在空间上整体呈现西安及其周边以及榆林北部能源区发展程度高,其余地区发展程度低的特点,且乡村转型发展经历了低度转型主导到较低、中度转型主导的发展过程。（2）地均固定资产投入、加权路网密度、人均生产总值、规模以上工业企业个数和人均耕地资源量是陕西省乡村转型发展的主要影响因素。（3）影响因素中除人均耕地资源量对乡村转型发展整体呈现负向影响外,其余因素均呈现正向影响,且对不同县域影响程度不同,影响效应的空间分异明显。研究对因地制宜地制定陕西省乡村转型发展的差异化政策措施具有重要的参考意义。     

Estimation of the accumulation rates and health risks of heavy metals in residential soils of three metropolitan cities in China

Heavy metal concentrations in urban soils are likely to increase over time because of continuous urbanization and heavy metal emissions. To estimate the accumulation rates of heavy metals in urban soils, we collected soil samples from residential areas with different building ages in the metropolitan cities of Shanghai, Shenzhen, and Beijing, China. Heavy metal concentrations in the soils varied among the cities and were primarily affected by soil parent material and the intensity of anthropogenic sources. Regression analyses revealed that the accumulation rates of Cd and Cu in the soils ranged from 0.0034 to 0.0039 mg/(kg•year) and 0.343 to 0.391 mg/(kg•year), respectively, and were similar across the three cities, while accumulation rates of Zn and Pb in Shanghai were higher than those in Shenzhen and Beijing. The higher accumulation rates of Zn and Pb in Shanghai can be explained by differences in city history and industrial structures among the cities. Residential soils with high health risks posed by the heavy metals were mostly collected from old towns of Shanghai because of high Pb content in the areas. Although recent urbanization resulted in elevated concentrations of Cd, Cu, Zn, and Pb in the residential soils, the effect on the total health risks of residents exposed to the soils was negligible.     

Support vector machine based prediction of photovoltaic module and power station parameters

ABSTRACT

The uncertainty in the output power of the photovoltaic (PV) power generation station due to variation in meteorological parameters is of serious concern. An accurate output power prediction of a PV system helps in better design and planning. The present study is carried out for the prediction of output power of PV generating station by using Support Vector Machines. Two cases are considered in the present study for prediction. Case-I deals with the prediction of PV module parameters such as V_oc, I_sh, R_s, R_sh, I_max, V_max, P_max, and case-II deals with the prediction of power generation parameters such as P_DC, P_AC, and system efficiency. Historical data of PV power station with an installed capacity of 10 MW and weather information are used as input to develop four different seasons-based SVM models for all parameters. The performance results of the models are presented in terms of Mean Relative Error (MRE) and Root Mean Square Error (RMSE). Additionally, the performance results obtained with polynomial and Radial Based Function kernel are also compared to show that which kernel has better prediction accuracy, and practicability. The result shows that the minimum average RMSE and MRE for case-I with Radial Based Function kernel are 0.034%, 0.055%, 0.002%, 1.726%, 0.044%, 0.047%, 2.342%, and 0.005%, 0.014%, 0.079%, 0.885%, 0.005%, 0.007%, 0.013%, and for case-II with poly kernel are 0.014%, 0.016%, 0.149% and 0.011%, 0.0175, 1.03%, respectively. The present study will be helpful to provide technical guidance to the prediction of the PV power System.     

Statistical Methods and Pitfalls in Environmental Data Analysis

This paper reviews four commonly used statistical methods for environmental data analysis and discusses potential pitfalls associated with application of these methods through real case study data. The four statistical methods are percentile and confidence interval, correlation coefficient, regression analysis, and analysis of variance (ANOVA). The potential pitfall for estimation of percentile and confidence interval includes the automatic assumption of a normal distribution to environmental data, which so often show a log-normal distribution. The potential pitfall for correlation coefficient includes the use of a wide range of data points in which the maximum in value may trivialize other smaller data points and consequently skew the correlation coefficient. The potential pitfall for regression analysis includes the propagation of uncertainties of input variables to the regression model prediction, which may be even more uncertain. The potential pitfall for ANOVA includes the acceptance of a hypothesis as a weak argument to imply a strong conclusion. As demonstrated in this paper, we may draw very different conclusions based on statistical analysis if the pitfalls are not identified. Reminder and enlightenment obtained from the pitfalls are given at the end of this article.     

A unique intelligent approach for forecasting project completion time in oil refineries

This study presents a hybrid approach for accurate forecasting of project completion time with noisy and uncertain safety factors in oil refineries. The hybrid approach is based on artificial neural network (ANN), fuzzy mathematical programming (FMP) and conventional regression. Three indictors, namely, number of occupational injuries, number of employees and ratio of maximum useful hours over useful hour per month are considered as inputs. Also, project completion time is considered as the main output. To achieve the objective of this study, five sets of data with respect to oil refinery construction projects in various cities of Iran are collected and analyzed through statistical methods. It is shown that for the actual case of this study, ANN presents lowest mean absolute percentage error (MAPE). Also, analysis of variance (ANOVA) is used to verify and validate the results of this study. This is the first study that presents a hybrid approach for accurate estimation and forecasting of project completion time with complex, noisy and uncertain occupational factors.