Institutional quality,financial development and sustainable economic growth among lower income countries

This article postulates strong endogenous relationships in lower income countries between institutional quality, financial development and sustained economic growth. These associations were investigated using the vector-error correction model (VECM) and Granger causality method for a sample of 79 countries from 2005 to 2022. The findings show that (1) these variables reinforce each other in the short run. (2) In the long run, both institutional quality and financial development can fuel economic growth. (3) The positive effect of institutional quality on economic growth is greater than that of financial development. Policy implications of these findings are that careful attention should be paid to co-development policies to enhance the institutional quality and the financial system in these economies. Policies should also consider economic growth strategies to enable sustainable economic growth rates.     

洪涝灾害条件下疏散交通生成预测方法

为有助于有关部门更准确预测洪涝灾害受灾民众的疏散量,结合非集计数据和集计数据的优点,提出分区集计数据的概念,设计了受灾区域分区方法,并通过意向偏好(SP)调查法对我国居民在洪涝条件下疏散交通需求数据进行调查。在此基础上,引入BP神经网络建立基于分区集计数据的疏散交通生成预测模型。利用调查数据进行实证分析发现,所设计方法取得了较好的预测效果,鲁棒性较好,平均相对预测误差仅为1.8%,其预测效果明显优于现有的非集计和整集计模型。     

基于复杂系统建模的水管理政策研究进展

基于Agent的建模方法（ABSS）通过自下而上的方式，考察系统中主体的不同状态和行为特征、主体与环境的作用、主体之间的作用，来表征系统的宏观特征，是进行复杂社会环境系统分析和政策研究的重要手段，在水资源、水环境管理系统中得到了有效的应用。本文在大量文献调研的基础上，讨论了ABSS建模方法的基本原理、主要特征、系统构成、分类方法和开发工具等特征，总结了其供水系统发展、水资源分配和流域水资源管理、农业土地和水资源利用、居民用水行为、农业污染控制及人类活动的水环境影响等方面的应用，分析了其在研究内容、研究方法、研究结果等方面的发展趋势，讨论了利用该方法研究我国水资源管理和水污染控制政策的必要性和重要性。     

SELECTING TREND TESTS FOR WATER QUALITY SERIES WITH SERIAL CORRELATION AND MISSING VALUES1

ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily.     

Community-Based Integrated Watershed Management

1 INTRODUCTIONIn the past, natural resources management initiatives havefocused on large but specific sector projects such as dams,reservoirs for water supply schemes, irrigation systems,crop production, at forestation, etc. Often these projectswere treated as technical and administrative issues ratherthan as a socio-economic and political one. However, thehigh social and environmental cost of such schemes haveled to a change of paradigm since the 1980s towards small-scale community projec…     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

ARSENIC CONSUMPTION AND HEALTH RISK PERCEPTIONS IN A RURAL WESTERN U.S. AREA1

ABSTRACT: Churchill County, Nevada, has approximately 23,000 residents, among whom an estimated 13,500 relied on private wells for water supply in 2002. This study examined exposure to arsenic in water supplies among residents with private domestic wells and factors related to householder choice to consume tap water. It compared opinions and concerns about water quality with consumption habits and observed concentrations from tap water samples. The results from 351 households indicated that a majority (75 percent) of respondents consumed tap water and that a minority (38 percent) applied treatment. Approximately 66 percent of those who consumed tap water were exposed to concentrations of arsenic that exceeded 10 ppb. Water consumption was related to application of treatment. Among 98 respondents who were not at all concerned about the health effects of aqueous arsenic, 59 (60 percent) reported consuming tap water with concentrations of arsenic exceeding 10 ppb. Conversely, among 86 respondents who were highly concerned about arsenic, 33 (37 percent) consumed tap water with concentrations of arsenic exceeding 10 ppb. Results from a national sampling effort showed that 620 of 5,304 private wells sampled (11.7 percent) had arsenic concentrations above 10 ppb. The paradox of awareness of arsenic in water supplies coupled with consumption of aqueous arsenic in concentrations greater than 10 ppb may be common in other parts of the nation. Enhanced educational efforts, especially related to tap water sampling and explanations of efficacy of available treatment, may be useful means of reducing exposure through private water supplies.     

跨行政区域水污染纠纷的对策探讨——剖析某水域水污染死鱼事故

针对某乡镇企业十分发达地区的跨行政(市县)区域水污染死鱼事故的剖析，本文提出了处理解决跨行政区域水污染纠纷事故的若干对策建议。     

COMPARISON OF STOCHASTIC AND DETERMINISTIC DYNAMIC PROGRAMMING FOR RESERVOIR OPERATING RULE GENERATION1

ABSTRACT: Two dynamic programming models — one deterministic and one stochastic — that may be used to generate reservoir operating rules are compared. The deterministic model (DPR) consists of an algorithm that cycles through three components: a dynamic program, a regression analysis, and a simulation. In this model, the correlation between the general operating rules, defined by the regression analysis and evaluated in the simulation, and the optimal deterministic operation defined by the dynamic program is increased through an iterative process. The stochastic dynamic program (SDP) describes streamflows with a discrete lag-one Markov process. To test the usefulness of both models in generating reservoir operating rules, real-time reservoir operation simulation models are constructed for three hydrologically different sites. The rules generated by DPR and SDP are then applied in the operation simulation model and their performance is evaluated. For the test cases, the DPR generated rules are more effective in the operation of medium to very large reservoirs and the SDP generated rules are more effective for the operation of small reservoirs.