Coupling a land use model and an ecosystem model for a crop-pasture zone

This paper describes the development of a land use model coupling ecosystem processes. For a given land use pattern in a region, a built-in regional ecosystem model (TESim) simulates leaf physiology of plants, carbon and nitrogen dynamics, and hydrological processes including runoff generation and run-on re-absorption, as well as runoff-induced soil erosion and carbon and nitrogen loss from ecosystems. The simulation results for a certain period from 1976 to 1999 were then used to support land use decisions and to assess the impacts of land use changes on environment. In the coupling model, the land use type for a land unit was determined by optimization of a weighted suitability derived from expert knowledge about the ecosystem state and site conditions. The model was applied to the temperate crop-pasture band in northern China (CCPB) to analyze the interactions between land use and major ecosystem processes and functions and to indicate the added value of the feedbacks by comparing simulations with and without the coupling and feedbacks between land use module and ecosystem processes. The results indicated that the current land use in CCPB is neither economical nor ecologically judicious. The scenario with feedbacks increased NPP by 46.78 g C m⁻² a⁻¹, or 32.23% of the scenario without feedbacks, also decreased soil erosion by 0.65 kg m⁻² a⁻¹, or 23.13%. Without altering the regional land use structure (proportions of each land use type). The system developed in this study potentially benefits both land managers and researchers.     

表面处理清洁生产线的研发

介绍了中国电器科学研究院近期研制开发的电镀、氧化等金属表面处理新型生产线。对生产线各相关系统进行研究,通过改进与创新,达到清洁、节能、智能化等目的。     

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.     

Reduction of dissolved organic matter in terms of DOC, UV-254, SUVA and THMFP in industrial estate wastewater treated by stabilization ponds

The aim of this research was to monitor the influent and effluent water quality of the aeration, facultative and oxidation water treatment ponds of an industrial estate. This industrial estate, the largest in northern Thailand, has proposed to utilization of reclaimed treated wastewater in their raw water supply so as to cope with the yearly water shortage during the dry season. Water samples were collected four times from four sampling points and evaluated for their dissolved organic matter (DOM) content in terms of dissolved organic carbon (DOC), ultraviolet light absorbance at 254 nm (UV-254), specific ultraviolet absorption (SUVA), trihalomethane formation potential (THMFP) and trihalomethane (THM) species. Average values of DOC, UV-254, SUVA and THMFP in the influent wastewater of 12.9 mg L⁻¹, 0.165 cm⁻¹, 1.29 L mg⁻¹m⁻¹ and 1.24 mg L⁻¹, respectively, were observed. The aeration ponds produced the best results: a 54% reduction of DOC, a 33% reduction of UV-254, and a 57% reduction of THMFP. However, SUVA in the aeration pond effluent showed a moderate increase. The facultative ponds and oxidation ponds did not take part in the reduction of DOC, UV-254, SUVA and THMFP. Average DOC, UV-254, SUVA and THMFP value of the treated wastewater were 5.8 mg L⁻¹, 0.107 cm⁻¹, 1.85 L mg⁻¹m⁻¹ and 468 μg L⁻¹, respectively. Chloroform, at 72.6% of total THMFP, was found to be the predominant THM species.     

Groundwater Pollution Around an Industrial Area in the Coastal Stretch of Maharashtra State, India

The main objective of this paper is to examine pollution threat, especially to the groundwater resources, around Tarapur industrial area (also called the Tarapur MIDC area) located on the Arabian Sea Coast in Thane District of Maharashtra State, India and suggest remedial measures that may also be relevant to other industrial areas on the Indian Sea Coast. One hundred and thirty one samples were collected from various sources, such as dugwells, borewells, dug-cum-borewells, effluent sumps, drainage channels (effluent channels), creeks and ocean, for chemical analyses. These analyses show that the area in general is characterized by hard water and high salinity hazard, possibly due to its proximity and hydraulic connection with the sea. Although the potability of groundwater is questionable in certain pockets, it is good enough for irrigation purposes at present. Low pH value and high heavy metal contents in the adjoining Muramba creek water is a matter of great concern and may be attributed to the indiscriminate disposal of industrial effluents to the drainage channels connecting the creek. Muramba Creek is well connected with the Arabian Sea, and there are evidences of seawater intrusion around this creek. Because of the fact that Muramba Creek is highly polluted, and is hydraulically connected with the dugwells and borewells surrounding the creek, it cannot be ruled out that the groundwater around this creek is susceptible to contamination. Unless measures are not taken immediately to stop the indiscriminate disposal of the solid wastes and liquid effluents in open ground and drainage channels, and measures are not taken to maintain the appropriate pH values at the effluent treatment facilities before their disposal, the problem would indeed be formidable one day, and it will be too late then for the authorities to take care of the resulting maladies. Few suggestions have been given for controlling and managing the industrial pollution around the Tarapur MIDC area. These suggestions are relevant to other industrial areas situated on the 7,000 km long Indian Sea Coast.     

环境保护利益博弈分析与实证——以长寿湖渔业养殖污染防治为例

运用博弈论和利益相关理论构建的环境保护利益博弈分析框架,剖析长寿湖渔业养殖污染中的利益相关者及其博弈。通过分析政府、企业、渔民之间的六种利益博弈形式,得出结论：在渔场的各种利益博弈中,渔民的驱利行为导致了长寿湖的“公地悲剧”;守法成本高于违法成本是环境执法不力的主要原因;对渔场企业的环境管理职能缺乏有效的激励和约束;现行的政绩考核制度导致政府部门在环境保护行为中政治利益失衡;环保政策必须与相应经济利益挂钩,用激励机制把环保内化为自觉的经济行为;合理引导环境主体的群体行为,会使环保工作更加有效开展。     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (− 0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Water sharing agreements sustainable to reduced flows

By signing a water sharing agreement (WSA), countries agree to release an amount of river water in exchange for a negotiated compensation. We examine the vulnerability of such agreements to reduced water flows. Among all WSAs that are acceptable to riparian countries, we find out the one which is self-enforced under the most severe drought scenarios. The so-called upstream incremental WSA assigns to each country its marginal contribution to its followers in the river. Its mirror image, the downstream incremental WSA, is not sustainable to reduced flow at the source. Self-enforcement problems can be solved by setting water releases and compensations contingent to water flow. We apply our analysis to the Aral Sea Basin. We compute the upstream incremental compensations for the Bishkek agreement and asses its vulnerability with historical flows.