Analyzing the cost effectiveness of Santiago, Chile's policy of using urban forests to improve air quality

Santiago, Chile has the distinction of having among the worst urban air pollution problems in Latin America. As part of an atmospheric pollution reduction plan, the Santiago Regional Metropolitan government defined an environmental policy goal of using urban forests to remove particulate matter less than 10 microm (PM(10)) in the Gran Santiago area. We used cost effectiveness, or the process of establishing costs and selecting least cost alternatives for obtaining a defined policy goal of PM(10) removal, to analyze this policy goal. For this study, we quantified PM(10) removal by Santiago's urban forests based on socioeconomic strata and using field and real-time pollution and climate data via a dry deposition urban forest effects model. Municipal urban forest management costs were estimated using management cost surveys and Chilean Ministry of Planning and Cooperation documents. Results indicate that managing municipal urban forests (trees, shrubs, and grass whose management is under the jurisdiction of Santiago's 36 municipalities) to remove PM(10) was a cost-effective policy for abating PM(10) based on criteria set by the World Bank. In addition, we compared the cost effectiveness of managing municipal urban forests and street trees to other control policies (e.g. alternative fuels) to abate PM(10) in Santiago and determined that municipal urban forest management efficiency was similar to these other air quality improvement measures.     

Ecological scenarios analyzed and evaluated by a shallow lake model

We applied the complex ecosystem model EMMO, which was adopted to the shallow lake Müggelsee (Germany), in order to evaluate a large set of ecological scenarios. By means of EMMO, 33 scenarios and 17 indicators were defined to characterize their effects on the lake ecosystem. The indicators were based on model outputs of EMMO and can be separated into biological indicators, such as chlorophyll-a and cyanobacteria, and hydro-chemical indicators, such as phosphorus. The question to be solved was, what is the ranking of the scenarios based on their characterization by these 17 indicators? And how can we handle high quantities of complex data within evaluation procedures? The scenario evaluation was performed by partial order theory which, however, did not provide a clear result. By subsequently applying the hierarchical cluster analysis (complete linkage) it was possible to reduce the data matrix to indicator and scenario representatives. Even though this step implies losses of information, it simplifies the application of partial order theory and the post processing by METEOR. METEOR is derived from partial order theory and allows the stepwise aggregation of indicators, which subsequently leads to a distinct and clear decision. In the final evaluation result the best scenario was the one which defines a minimum nutrient input and no phosphorus release from the sediment while the worst scenario is characterized by a maximum nutrient input and extensive phosphorus release from the sediment. The reasonable and comprehensive results show that the combination of partial order, cluster analysis and METEOR can handle big amounts of data in a very clear and transparent way, and therefore is ideal in the context of complex ecosystem models, like that we applied.     

Validation of a hybrid life-cycle inventory analysis method

The life-cycle inventory analysis step of a life-cycle assessment (LCA) may currently suffer from several limitations, mainly concerned with the use of incomplete and unreliable data sources and methods of assessment. Many past LCA studies have used traditional inventory analysis methods, namely process analysis and input-output analysis. More recently, hybrid inventory analysis methods have been developed, combining these two traditional methods in an attempt to minimise their limitations. In light of recent improvements, these hybrid methods need to be compared and validated, as these too have been considered to have several limitations. This paper evaluates a recently developed hybrid inventory analysis method which aims to improve the limitations of previous methods. It was found that the truncation associated with process analysis can be up to 87%, reflecting the considerable shortcomings in the quantity of process data currently available. Capital inputs were found to account for up to 22% of the total inputs to a particular product. These findings suggest that current best-practice methods are sufficiently accurate for most typical applications, but this is heavily dependent upon data quality and availability. The use of input-output data assists in improving the system boundary completeness of life-cycle inventories. However, the use of input-output analysis alone does not always provide an accurate model for replacing process data. Further improvements in the quantity of process data currently available are needed to increase the reliability of life-cycle inventories.     

An approach to optimise nutrient management in environmental sanitation systems despite limited data

The material flow analysis method can be used to assess the impact of environmental sanitation systems on resource consumption and environmental pollution. However, given the limited access to reliable data, application of this data-intensive method in developing countries may be difficult. This paper presents an approach allowing to develop material flow models despite limited data availability. Application of an iterative procedure is of key importance: model parameter values should first be assessed on the basis of a literature review and by eliciting expert judgement. If model outputs are not plausible, sensitive input parameters should be reassessed more accurately. Moreover, model parameters can be expressed as probability distributions and variable uncertainty estimated by using Monte Carlo simulation. The impact of environmental sanitation systems on the phosphorus load discharged into surface water in Hanoi, Vietnam, is simulated by applying the proposed approach.     

A Cost-Effectiveness Analysis of Seminatural Wetlands and Activated Sludge Wastewater-Treatment Systems

A cost-effectiveness analysis was performed to evaluate the competitiveness of seminatural Free Water Surface (FWS) wetlands compared to traditional wastewater-treatment plants. Six scenarios of the service costs of three FWS wetlands and three different wastewater-treatment plants based on active sludge processes were compared. The six scenarios were all equally effective in their wastewater-treatment capacity. The service costs were estimated using real accounting data from an experimental wetland and by means of a market survey. Some assumptions had to be made to perform the analysis. A reference wastewater situation was established to solve the problem of the different levels of dilution that characterize the inflow water of the different systems; the land purchase cost was excluded from the analysis, considering the use of public land as shared social services, and an equal life span for both seminatural and traditional wastewater-treatment plants was set. The results suggest that seminatural systems are competitive with traditional biotechnological systems, with an average service cost improvement of 2.1-fold to 8-fold, according to the specific solution and discount rate. The main improvement factor was the lower maintenance cost of the seminatural systems, due to the self-regulating, low artificial energy inputs and the absence of waste to be disposed. In this work, only the waste-treatment capacity of wetlands was considered as a parameter for the economic competitiveness analysis. Other goods/services and environmental benefits provided by FWS wetlands were not considered.

Should Habitat Trading Be Based on Mitigation Ratios Derived from Landscape Indices? A Model-Based Analysis of Compensatory Restoration Options for the Red-Cockaded Woodpecker

Many species of conservation concern are spatially structured and require dispersal to be persistent. For such species, altering the distribution of suitable habitats on the landscape can affect population dynamics in ways that are difficult to predict from simple models. We argue that for such species, individual-based and spatially explicit population models (SEPMs) should be used to determine appropriate levels of off-site restoration to compensate for on-site loss of ecologic resources. Such approaches are necessary when interactions between biologic processes occur at different spatial scales (i.e., local [recruitment] and landscape [migration]). The sites of restoration and habitat loss may be linked to each other, but, more importantly, they may be linked to other resources in the landscape by regional biologic processes, primarily migration. The common management approach for determining appropriate levels of off-site restoration is to derive mitigation ratios based on best professional judgment or pre-existing data. Mitigation ratios assume that the ecologic benefits at the site of restoration are independent of the ecologic costs at the site of habitat loss. Using an SEPM for endangered red-cockaded woodpeckers, we show that the spatial configuration of habitat restoration can simultaneously influence both the rate of recruitment within breeding groups and the rate of migration among groups, implying that simple mitigation ratios may be inadequate.     

室内甲醛污染影响因素的多元回归分析

本文在室内甲醛质量守恒定律基本公式合理推导的基础上,对影响甲醛浓度的主要因素做了正交实验。对实验数据进行多元回归分析,建立室内甲醛浓度预测模型。对模型做检验,检验结果表明,本文的预测模型能较好地预测室内空气中的甲醛浓度。     

Evaluation of the temporal variations of air quality in Taipei City, Taiwan, from 1994 to 2003

Data collected from the five air-quality monitoring stations established by the Taiwan Environmental Protection Administration in Taipei City from 1994 to 2003 are analyzed to assess the temporal variations of air quality. Principal component analysis (PCA) is adopted to convert the original measuring pollutants into fewer independent components through linear combinations while still retaining the majority of the variance of the original data set. Two principal components (PCs) are retained together explaining 82.73% of the total variance. PC1, which represents primary pollutants such as CO, NO(x), and SO(2), shows an obvious decrease over the last 10 years. PC2, which represents secondary pollutants such as ozone, displays a yearly increase over the time period when a reduction of primary pollutants is obvious. In order to track down the control measures put forth by the authorities, 47 days of high PM(10) concentrations caused by transboundary transport have been eliminated in analyzing the long-term trend of PM(10) in Taipei City. The temporal variations over the past 10 years show that the moderate peak in O(3) demonstrates a significant upward trend even when the local primary pollutants have been well under control. Monthly variations of PC scores demonstrate that primary pollution is significant from January to April, while ozone increases from April to August. The results of the yearly variations of PC scores show that PM(10) has gradually shifted from a strong correlation with PC1 during the early years to become more related to PC2 in recent years. This implies that after a reduction of primary pollutants, the proportion of secondary aerosols in PM(10) may increase. Thus, reducing the precursor concentrations of secondary aerosols will be an effective way to lower PM(10) concentrations.     

A process integration approach to industrial water conservation: a case study for a Chinese steel plant

A systematic approach to optimizing water network has traditionally been utilized to exam and plan water conservation in industrial processes. In the present case study, water-pinch technology was used to analyze and optimize the water network of a steel plant near China's Zhangjiakou city. A system design was developed and a limiting constraint (Cl(-) concentration) was identified based on investigations of water quality then the minimum freshwater and wastewater targets were determined without considering water losses. The analysis was then extended by calculating the additional input of freshwater required to balance the actual water losses. A nearest-neighbor algorithm (NNA) was used to distribute the freshwater and recycled water among each of the plant's operations. The results showed that with some reconstruction of the water network, the flow rates of freshwater and wastewater could be decreased by 57.5% and 81.9%, respectively.     

Cluster analysis and quality assessment of logged water at an irrigation project, eastern Saudi Arabia

A multivariate statistical technique, cluster analysis, was used to assess the logged surface water quality at an irrigation project at Al-Fadhley, Eastern Province, Saudi Arabia. The principal idea behind using the technique was to utilize all available hydrochemical variables in the quality assessment including trace elements and other ions which are not considered in conventional techniques for water quality assessments like Stiff and Piper diagrams. Furthermore, the area belongs to an irrigation project where water contamination associated with the use of fertilizers, insecticides and pesticides is expected. This quality assessment study was carried out on a total of 34 surface/logged water samples. To gain a greater insight in terms of the seasonal variation of water quality, 17 samples were collected from both summer and winter seasons. The collected samples were analyzed for a total of 23 water quality parameters including pH, TDS, conductivity, alkalinity, sulfate, chloride, bicarbonate, nitrate, phosphate, bromide, fluoride, calcium, magnesium, sodium, potassium, arsenic, boron, copper, cobalt, iron, lithium, manganese, molybdenum, nickel, selenium, mercury and zinc. Cluster analysis in both Q and R modes was used. Q-mode analysis resulted in three distinct water types for both the summer and winter seasons. Q-mode analysis also showed the spatial as well as temporal variation in water quality. R-mode cluster analysis led to the conclusion that there are two major sources of contamination for the surface/shallow groundwater in the area: fertilizers, micronutrients, pesticides, and insecticides used in agricultural activities, and non-point natural sources.