Hiking Trails and Tourism Impact Assessment In Protected Area: Jiuzhaigou Biosphere Reserve,China

More and more visitors are attracted to protected areas nowadays, which not only bring about economic increase but also seriously adverse impacts on the ecological environment. In protected areas, trails are linkage between visitors and natural ecosystem, so they concentrate most of the adverse impacts caused by visitors. The trampling problems on the trails have been received attentions in the tremendous researches. However, few of them have correlated the environmental impacts to trail spatial patterns. In this project, the trails were selected as assessment objective, the trampling problems trail widening, multiple trail, and root exposure were taken as assessment indicators to assess ecological impacts in the case study area Jiuzhaigou Biosphere Reserve, and two spatial index, connectivity and circularity, were taken to indicate the trail network spatial patterns. The research results showed that the appearing frequency of the trampling problems had inverse correlation with the circularity and connectivity of the trail network, while the problem extent had no correlation with the spatial pattern. Comparing with the pristine trails, the artificial maintenance for the trails such as wooden trails and flagstone trails could prohibit vegetation root from exposure effectively. The research finds will be useful for the future trail design and tourism management.     

Energy Expenditure in Egypt: Empirical Evidence Based on a Quantile Regression Approach

Environmental Modeling & Assessment - This paper investigates the key factors affecting household energy expenditure in Egypt. Based upon the latest 2015 Egyptian HIECS Survey, we develop a...     

A Decision Support System Approach for Rivers Monitoring and Sustainable Management

This paper presents a Decision Support System (DSS) approach developed in the context of the Copernicus project entitled System for Water Monitoring and Sustainable Management based on Ground Stations and Satellite Images (WATERMAN). The main objective of WATERMAN is the monitoring and management of the Strymon River in the Southern Balkans. The specific DSS integrates the main components of WATERMAN and helps the decision maker to monitor the Strymon region; to control and forecast the quantity and quality of the river water; as well as to make objective decisions about the state of the water based on data provided by radio computers, earth stations and satellite images processed by mathematical and statistical models and Geographical Information Systems (GIS).     

Volatile Organic Compounds in the Area of Madrid: A Chemometrical Approach

Multivariate techniques have been applied to the set of dataobtained after one year sampling of volatile organic compounds(VOCs), including volatile aldehydes in the area of Madrid inorder to evaluate the possible correspondence among groups ofanalysed compounds, as far as modelling of different emissionsources in relation to location and season. The measurements were carried out at four sites in Madrid, characteristic for urban and suburban areas. Additionally, as reference, a rural area 100 km far from the city was considered. Results of correlation analysis, factor and cluster analysis are presented.Higher correlations were found between variables related withtraffic emissions. Factor analysis results showed two mainsignificant variables related to anthropogenic and biogenicemissions respectively. In relation to cluster analysis, samples were grouped according to sampling site and seasonal variations.     

Sustainable natural resource management and environmental assessment in the Salt Lake (Tuz Golu) Specially Protected Area

The Salt Lake Specially Protected Area is a unique ecosystem for both agricultural activities and natural life in Turkey. In the present study, an attempt was made to develop a conceptual land use strategy and methodology, taking into account ecological factors for regional development in the Salt Lake Specially Protected Area. A detailed Geographic Information System (GIS) analysis was done to create a comprehensive database including land use, land suitability, and environmental factors (soil, climate, water quality, fertilizing status, and heavy metal and pesticide pollution). The results of the land suitability survey for agricultural use showed that, while 62.6% of the study area soils were classified as best and relatively good, about 15% were classified as problematic and restricted lands, only 22.2% of the study area soils were not suitable for agricultural uses. However, this is not enough to derive maximum benefit with minimum degradation. Therefore, environmental factors and ecological conditions were combined to support this aim and to protect the ecosystem. Excessive irrigation practices, fertilizer and pesticide application, and incorrect management practices all accelerate salinization and degradation. In addition to this, it was found that a multi-layer GIS analysis made it easy to develop a framework for optimum land use and could increase the production yield preserving the environmental conditions. Finally, alternative management and crop patterns were undertaken to sustain this unique ecosystem, considering water, soil, climate, land use characteristics, and to provide guidance for planners or decision makers.     

Integrated Traffic and Emission Simulation: a Model Calibration Approach Using Aggregate Information

Environmental impacts of road traffic have attracted increasing attention in project-level traffic planning and management. The conventional approach considers emission impact analysis as a separate process in addition to traffic modeling. This paper first introduces our research effort to integrate traffic, emission, and dispersion processes into a common distributed computational framework, which makes it efficient to quantify and analyze correlations among dynamic traffic conditions, emission impacts, and air quality consequences. A model calibration approach is particularly proposed when on-road or in-lab instantaneous emission measurements are not directly available. Microscopic traffic simulation is applied to generate dynamic vehicle states at the second-by-second level. Using aggregate emission estimation as standard reference, a numerical optimization scheme on the basis of a stochastic gradient approximation algorithm is applied to find optimal parameters for the dynamic emission model. The calibrated model has been validated on several road networks with traffic states generated by the same simulation model. The results show that with proper formulation of the optimization objective function, the estimated dynamic emission model can capture the trends of aggregate emission patterns of traffic fleets and predict local emission and air quality at higher temporal and spatial resolutions.     

Water Quality Prediction of Water Sources Based on Meteorological Factors using the CA-NARX Approach

With the increasingly serious problem of surface water environmental safety, it is of great significance to study the changing trend of reservoir water quality, and it is necessary to establish a water quality prediction and early warning system for the management and maintenance of water resources. Aiming at the problem of water quality prediction in reservoirs, a CA-NARX algorithm is designed, which combines the improved dynamic clustering algorithm with the idea of machine learning and the forward dynamic regression neural network. The improved dynamic clustering algorithm is used to classify the eutrophication degree of waterbodies according to the total phosphorus and total nitrogen content. Considering four meteorological factors, air temperature, water temperature, water surface evaporation, and rainfall, synthetically for each water quality condition, the total phosphorus and total nitrogen in the waterbody are forecasted by an improved forward NARX dynamic regression neural network. Based on this, the CA-NARX prediction algorithm can realize short period water quality prediction. Compared with the traditional support vector regression machine model, improved GA-BP neural network, and exponential smoothing method, the CA-NARX model has the least prediction error.

     

A Multiple Criteria Decision Analysis Model Based on ELECTRE TRI-C for Erosion Risk Assessment in Agricultural Areas

This paper deals with a real-world decision-aiding problem for zoning the risk of erosion, total suspended solids emissions, and ecological consequences of their transfers towards the streams. One of these consequences is the decrease of fishes into the streams in agricultural watersheds, because of the clogging of spawning areas. Given the multiple criteria nature of the problem, the originality of our research is to adapt a new decision-aiding sorting method, ELECTRE TRI-C, for identifying risk zones in rural areas, where measures must be taken. The developed model was applied in a small watershed (Low Normandy, France) where the objective was to assess the most appropriate intervention for protecting the reproduction habitat of the salmonid fishes. Agricultural parcels were evaluated on multiple criteria for grouping them into four risk categories, which are related to risk levels as well as priorities on the improvement works. The decision-aiding sorting model is co-constructed, within a constructive approach, through an interaction process between decision-aiding analysts, environmental experts, and local actors for improving transparency and communication on the results. This model is linked with a geographical information system (GIS) for assessing a set of criteria and the visualization of the farming parcels along with their type of intervention they should be submitted to best practices. The assignment results were validated by the environmental experts. These results have a strong impact on the agricultural practices of the farmers into the watersheds. The model proposed in this paper can be considered as a useful decision aid tool in any regions for implementing public agricultural and environmental policies for protecting the ecological areas.     

Attitude Towards Risk and Production Decision: an Empirical Analysis on French Private Forest Owners

This paper deals with the forest owner’s attitude towards risk and the harvesting decision in several ways. First, we propose to characterize and quantify the forest owner’s attitude towards risk. Second, we analyze the determinants of the forest owner’s risk attitude. Finally, we determine the impact of the forest owner’s risk attitude on the harvesting decision. The French forest owner’s risk attitude is tackled by implementing a questionnaire, including a context-free measure borrowed from experimental economics. The determinants of the forest owner’s risk attitude and harvesting decision are estimated through a recursive bivariate ordered probit model. We show that French forest owners are characterized by a relative risk aversion coefficient close to 1 with a DARA assumption. In addition, we find that the forest owner’s risk aversion is influenced positively and significantly by the level of risk exposure, the geographical location of the forest and the fact to be a forester, and negatively by the income. Finally, we obtain that the forest owner’s risk aversion has a positive and significant impact on the harvesting decision.     

浅析新疆环境应急管理与决策支持系统

针对在处理、处置突发性环境污染事故中存在的突出问题,阐述了利用GIS等技术在设计开发新疆环境应急管理与决策支持系统的总体设计理念,对其总体应用框架、主要应用功能等进行了分析。该系统设计既满足应急管理需要又考虑了污染源日常管理的工作需要,将在实际应用中发挥重要作用。     

Modelling Environmental Risk Using the Upper Partial Moment: a Safety-First Approach

The objective of the paper is to model economic-environmental trade-offs using a safety-first approach. The novelty of the approach is in the use of the empirically estimated flexible production risk and environmental risk functions that create a clear link between the source of the pollution, the production risk due to input use and the environmental outcome. Simulated production data and an environmental indicator were used to estimate a production function and environmental response function for every production year. The response functions were incorporated into an upper partial moment model, which ensures compliance to the user-specified environmental goal by enforcing the environmental constraint. Production decisions are significantly impacted by the presence of an environmental constraint due to the substantial compliance costs. Any changes in the intensive and extensive margin made by risk-averse decision-makers impact the size of the compliance cost faced by producers. The presence of an environmental constraint impact production decisions significantly with substantial compliance costs. While, fertiliser application technique have very little effect on the size of compliance costs. The greatest difference in compliance cost is therefore due to changes in the use of fixed resources.     

Development and Validation of Ecological Indicators: an ORD Approach

The U. S. Environmental Protection Agency's Office of Research and Development (ORD) is continuing research efforts initiated by the Environmental Monitoring and Assessment Program on ecological indicator development. An ORD Ecological Indicators Working Group has been formed with activities in three primary areas. (1) Guidelines and procedures are being developed to evaluate indicators for use in monitoring programs. Indicators will be evaluated on conceptual soundness, implementation, response variability, and interpretation/utility. The evaluation guidelines will be applied in peer review to endorse technically acceptable indicators and will provide research direction for improvements. (2) An ORD strategy for research in ecological indicators is being developed by the Working Group in collaboration with Division research scientists. The strategy will serve to prioritize research based on the greatest importance and uncertainty and identify goals for indicator development in both intramural and extramural programs. The research strategy includes application of the evaluation guidelines to identify relevant research questions. (3) Interactions with indicator client and user groups (states, program offices and regions) are actively being sought for successful development and implementation of indicators. Client indicator priorities are formally included in the research strategy and user feedback on indicators will help to identify relevant research questions. Consultations with users will serve to assist in evaluating, implementing, and interpreting indicators in monitoring programs.     

Development of a New Approach to Cumulative Effects Assessment: A Northern River Ecosystem Example

If sustainable development of Canadian waters is to be achieved, a realistic and manageable framework is required for assessing cumulative effects. The objective of this paper is to describe an approach for aquatic cumulative effects assessment that was developed under the Northern Rivers Ecosystem Initiative. The approach is based on a review of existing monitoring practices in Canada and the presence of existing thresholds for aquatic ecosystem health assessments. It suggests that a sustainable framework is possible for cumulative effects assessment of Canadian waters that would result in integration of national indicators of aquatic health, integration of national initiatives (e.g., water quality index, environmental effects monitoring), and provide an avenue where long-term monitoring programs could be integrated with baseline and follow-up monitoring conducted under the environmental assessment process.     

A Landscape Approach for Detecting and Evaluating Change in a Semi-Arid Environment

Vegetation change in the American West has been a subject of concern throughout the twentieth century. Although many of the changes have been recorded qualitatively through the use of comparative photography and historical reports, little quantitative information has been available on the regional or watershed scale. It is currently possible to measure change over large areas and determine trends in ecological and hydrological condition using advanced space-based technologies. Specifically, this process is being tested in a community-based watershed in southeast Arizona and northeast Sonora, Mexico using a system of landscape pattern measurements derived from satellite remote sensing, spatial statistics, process modeling, and geographic information systems technology. These technologies provide the basis for developing landscape composition and pattern indicators as sensitive measures of large-scale environmental change and thus may provide an effective and economical method for evaluating watershed condition related to disturbance from human and natural stresses. The project utilizes the database from the North American Landscape Characterization (NALC) project which incorporates triplicate Landsat Multi-Spectral Scanner (MSS) imagery from the early 1970s, mid 1980s, and the 1990s. Landscape composition and pattern metrics have been generated from digital land cover maps derived from the NALC images and compared across a nearly 20-year period. Results about changes in land cover for the study period indicate that extensive, highly connected grassland and desertscrub areas are the most vulnerable ecosystems to fragmentation and actual loss due to encroachment of xerophytic mesquite woodland. In the study period, grasslands and desertscrub not only decreased in extent but also became more fragmented. That is, the number of grassland and desertscrub patches increased and their average patch sizes decreased. In stark contrast, the mesquite woodland patches increased in size, number, and connectivity. These changes have important impact for the hydrology of the region, since the energy and water balance characteristics for these cover types are significantly different. The process demonstrates a simple procedure to document changes and determine ecosystem vulnerabilities through the use of change detection and indicator development, especially in regard to traditional degradation processes that have occurred throughout the western rangelands involving changes of vegetative cover and acceleration of water and wind erosion.     

Assessing a Quick Monitoring Method Using Rocky Intertidal Communities as a Bioindicator: A Multivariate Approach in Algeciras Bay

A multivariate approach was used to test the value of intertidal communities as a bioindicator of environmental conditions at Algeciras Bay, southern Spain. The study area is located in the Strait of Gibraltar and it is subjected to a variety of anthropic impacts. Eight localities (5 inside and 3 outside the bay) were selected, and four transects were undertaken in each locality to characterise the fauna and flora. The spatial distribution of the intertidal species reflected the physico-chemical conditions of Algeciras Bay. The stations located outside the bay, characterised by high hydrodynamism and dissolved oxygen and low sedimentation and turbidity, had a higher diversity and species richness than the inner stations. According to the BIO-ENV procedure and CCA, water turbidity was the factor which best correlated with the intertidal assemblages. SIMPER showed that the molluscs Chtamalus stellatus, Mytilus cf edulis, Littorina neritoides and Balanus perforatus, and the algae Gelidium pusillum, Corallina elongata, Asparagopsis armata, Colpomenia sinuosa and Fucus spiralis were the species that most contributed to the dissimilarity between internal and external sites. The present study, based on the spatial distribution of intertidal taxa, yielded similar results to those previously obtained in the area with costly physico-chemical analysis based on complex matrices of subtidal epifaunal communities. Consequently, the intertidal sampling method proposed in this study is presented here as a quick, effective alternative strategy, and can be useful in environmental monitoring programs, since these communities are easily accessible and amenable to sample, and the sessile nature of the majority of the species makes future, long-term monitoring relatively simple.     

Energy Security: A Robust Optimization Approach to Design a Robust European Energy Supply via TIAM-WORLD

Energy supply routes to a given region are subject to random events, resulting in partial or total closure of a route (corridor). For instance, a pipeline may be subject to technical problems that reduce its capacity. Or, oil supply by tanker may be reduced for political reasons or because of equipment mishaps at the point of origin or again, by a conscious decision by the supplier in order to obtain economic benefits. The purpose of this article is to formulate a simplified version of the above issue that mainly addresses long-term uncertainties. The formulation is done via a version of the TIAM-WORLD Integrated Model, modified to implement the approach of robust optimization. In our case, the approach can be interpreted as a revival of chance-constrained programming under the name of distributionally robust, or ambiguous, chance-constrained programming. We apply the approach to improve the security of supply to the European Energy system. The resulting formulation provides several interesting features regarding the security of EU energy supply and has also the advantage to be numerically tractable.