试论肥料对农业与环境的影响

以肥料的发展先后，将肥料的发展历史分为有机时代、无机时代和有机无机复合时代；论述肥料对农业和环境的影响，并对未来肥料的发展提出预测和展望。从长远的发展来看，生物肥料不仅可以节省自然资源，而且还可在有机无机复合肥和控释肥料的基础上，以有机复合肥作为基质，利用控释肥料的包膜剂、粘着剂等进行生物肥料优化组合；可以说生物复合肥料将是未来肥料发展的主流。可以预料，未来肥料是实现清洁生产、物质循环、持续发展的中心环节。它不仅可以消纳转化上农业生产和现代生活所产生的废物，而且它所投入的有机复合肥，也是一种对环境友好的绿色肥料。     

Biological hydrogen production from organic wastewater by dark fermentation in China: Overview and prospects

Biological hydrogen production by dark fermentation is an important part of biological hydrogen production technologies. China is a typical developing country that heavily relies on fossil fuels; thus, new, clean, and sustainable energy development turns quite urgent. It is delightful that Chinese government has already drawn up several H₂ development policies since 1990s and provided financial aid to launch some H₂ development projects. In this paper, the research status on dark fermentative hydrogen production in China was summarized and analyzed. Subsequently, several new findings and achievements, with some of which transformed into scale-up tests, were highlighted. Moreover, some prospecting coupling processes with dark fermentation of hydrogen production were also proposed to attract more research interests in the future.     

Exurban development

Exurbia, the rural area beyond the built-up urban and contiguous suburban area, is being developed rapidly with attendant losses in habitat and ecosystem services. This paper analyzes a spatial dynamic model with two production technologies for residential development—municipal sewer service for suburban development and septic systems for exurban development. In outlying agricultural areas, the additional sewer extension costs can significantly reduce the value of agricultural land in suburban use. Exurban development, while at lower density, can occur immediately and requires only the onsite conversion costs of septic systems. Hence, the willingness to pay for exurban use from households with higher preferences for lot size may exceed the agricultural landowner's reservation price on future suburban use for a range of distances from the city boundary. This results in a “feasible zone” for exurban leapfrog development and another fundamental reason for scattered development in the urban–rural fringe.     

An econometric model of the U.S. secondary copper industry: Recycling versus disposal

In this paper, a theoretical model of secondary recovery is developed that integrates microeconomic theories of production and cost with a dynamic model of scrap generation and accumulation. The model equations are estimated for the U.S. secondary copper industry and used to assess the impacts that various policies and future events have on copper recycling rates. The alternatives considered are: subsidies for secondary production, differing energy costs, and varying ore quality in primary production.     

Integrierte Treibhausgasbewertung der Prozessketten von Erdgas und industriellem Biomethan in Deutschland

Background The use of natural gas has increased in the last years. In the future, its import supply and transport structure will diversify (longer distances, higher share of LNG (liquefied natural gas), new pipelines). Thus the process chain and GHG emissions of the production, processing, transport and distribution might change. Simultaneously, the injection of bio methane into the natural gas grid is becoming more important. Although its combustion is regarded as climate neutral, during the production processes of bio methane GHG emissions are caused. The GHG emissions occurring during the process chain of energy fuels are relevant for the discussion on climate policy and decision making processes. They are becoming even more important, considering the new Fuel Quality Directive of the EU (Dec. 2008), which aims at controlling emissions of the fuel process chains. Aim In the context of the aspects outlined above the aim is to determine the future development of gas supply for Germany and the resulting changes in GHG emissions of the whole process chain of natural gas and bio methane. With the help of two gas consumption scenarios and an LCA of bio methane, the amount of future emissions and emission paths until 2030 can be assessed and used to guide decision processes in energy policy. Results and discussion The process chain of bio methane and its future technical development are outlined and the related emissions calculated. The analysis is based on an accompanying research study on the injection of bio methane to the German gas grid. Two types of biogas plants have been considered whereof the “optimised technology” is assumed to dominate the future market. This is the one which widely exploits the potential of process optimisation of the current “state of the art” plant. The specific GHG emissions of the process chain can thus be nearly halved from currently 27.8?t CO₂-eq./TJ to 14.8?t CO₂-eq./TJ in 2030. GHG emissions of the natural gas process chain have been analysed in detail in a previous article. Significant modifications and a decrease of specific emissions is possible, depending on the level of investment in the modernisation of the gas infrastructure and the process improvements. These mitigation options might neutralise the emission increase resulting from longer distances and energy intensive processes. In the last section two scenarios (low and high consumption) illustrate the possible development of the German gas supply until 2030, given an overall share of 8–12?% of bio methane. Considering the dynamic emission factors calculated in the former sections, the overall gas emissions and average specific emissions of German gas supply can be given. The current emissions of 215.4 million t CO₂-eq. are reduced by 25?% in the low-consumption scenario (162 million t CO₂-eq.), where consumption is reduced by 17?%. Assuming a consumption which is increased by 17?% in 2030, emissions are around 7?% higher (230.9 million t CO₂-eq.) than today. Conclusions Gaseous fuels will still play a significant role for the German energy supply in the next two decades. The GHG emissions mainly depend on the amount of gas used. Thus, energy efficiency will be a key issue in the climate and energy related policy discussion. A higher share of bio methane and high investments in mitigation and best available technologies can significantly reduce the emissions of the process chain. The combustion of bio methane is climate neutral compared to 56?t CO₂/TJ caused by the direct combustion of natural gas (or 111?t CO₂/TJ emitted by lignite). The advantage of gaseous energy carriers with the lowest levels of GHG emissions compared to other fossil fuels still remains. This holds true for fossil natural gas alone as well as for the expected future blend with bio-methane.     

生物制氢最新研究进展与发展趋势

氢能具有清洁、高效、可再生的特点,是一种最具发展潜力的化石燃料替代能源.与传统的热化学和电化学制氢技术相比,生物制氢具有低能耗、少污染等优势.近年来,生物制氢技术在发酵菌株筛选、产氢机制、制氢工艺等方面取得了较大进展.暗发酵和光发酵结合制氢技术是一种新技术,具有较高的氢气产量.以厌氧细菌和光合细菌为发酵菌种,以富含碳水化合物的工农业废弃物为原料,进行暗发酵和光发酵结合制氢,具有广阔发展前途前景.本文综述了国内外生物制氢技术研究进展,展望了未来发展趋势.     

A sustainable development metric based on youth

Nearly two decades ago, the World Bank declared achieving sustained and equitable development to be the greatest challenge facing the human race. In this article, an index of youth investment (IYI) is proposed to highlight children and the intergenerational dimension of sustainable development. The index incorporates quality-adjusted measures for child health and education. Comparisons with two complementary indicators of sustainable development, the human development index (HDI) and the adjusted net saving rate (AS), are made. A cross-section of 34 nations for 2006 is used as an illustration. A discussion of policies for promoting sustainable development through investing in children concludes the article.     

Exploring the future of European crop production in a liberalised market, with specific consideration of climate change and the regional competitiveness

Long-term future development of European agriculture within the global market is highly uncertain, but can potentially have large impacts on the future of agricultural businesses, rural communities and amenities such as traditional landscapes and biodiversity. Despite great uncertainties it is of interest to explore the extent of these potential changes. This paper provides an explorative scenario of the European crop production in a liberalised world without European Union (EU) market interventions. The results do not form a prediction or a business as usual scenario, but rather a plausible and salient thought-experiment of a possible future based on the consistent integration of current conceptual and quantitative models.Future scenarios for climate, demography, technology and global demand for agricultural commodities are used to assess the competitiveness of European agriculture. Regional economic competitiveness is determined by combining indicators for the economic strength of farms in a region and population pressure on agricultural land, and subsequently used to determine where agricultural production is likely to sustain under the market liberalisation scenario. The method is illustrated for the 27 EU member state countries for three commodities: wheat, potato and milk (relying on grass).Results include maps of the dominant wheat, potato and milk producing regions across Europe as projected for 2050. They show that due to increased agricultural productivity, less agricultural land will be needed to supply the European demand for food and feed. In addition, production will concentrate in those regions which have a comparative advantage. This potentially leads to a strong polarisation between north-western Europe and southern Europe, which faces negative impacts of climate change and central and northern Europe where agricultural businesses lag in economic strength and farm size. A contrasting policy intervention scenario illustrates how differences in demand and productivity result in an expansion of the agricultural area, especially for the production of wheat.Although the complete liberalisation scenario may seem unlikely, and the underlying assumptions have great uncertainty, the results help identify and map market pressures on agricultural land use across regions in Europe. As such, it stimulates policy debate on the desired future for the European agricultural sector and the trade-offs between economic competitiveness under global market conditions and policy intervention. In addition, it provides a basis for the planning of alternative economic strategies for agriculturally less competitive regions.     

污染物对鱼类的甲状腺激素干扰效应及其作用机制

环境中可以影响生物体甲状腺激素合成、运输、作用和代谢等过程的化学污染物称为甲状腺激素干扰物(TDCs),TDCs被认为是继环境雌激素之后最重要的一类内分泌干扰物.鱼类甲状腺的结构、甲状腺激素的转运和功能等与哺乳动物有较大差别.与哺乳动物相比,污染物干扰鱼类甲状腺激素的研究还较为缺乏.在介绍鱼类甲状腺结构、功能以及甲状腺激素在鱼体内动态过程的基础上,分析了污染物对鱼类的甲状腺激素干扰效应及其作用机制,探讨了今后鱼类甲状腺激素干扰研究的主要方向.污染物能对鱼类甲状腺激素水平、相关酶活性及甲状腺结构等产生直接影响;同时,污染物还可以通过干扰鱼类甲状腺系统对由甲状腺激素调节的重要生理过程如生长、繁殖和发育等产生间接影响.污染物主要通过干扰鱼类甲状腺激素的合成与分泌、转运、清除以及与甲状腺激素受体(TR)的相互作用等机制对鱼类产生不利影响.在污染物对鱼类甲状腺激素干扰的研究中,今后应重点关注环境中"新型"卤化有机污染物、鱼类早期发育过程与甲状腺激素干扰效应的关系、TR介导机制以及TDCs的筛选方法等.     

Application of eco-exergy for assessment of ecosystem health and development of structurally dynamic models

Eco-exergy has been widely used in the assessment of ecosystem health, parameter estimations, calibrations, validations and prognoses. It offers insights into the understanding of ecosystem dynamics and disturbance-driven changes. Particularly, structurally dynamic models (SDMs), which are developed using eco-exergy as the goal function, have been applied in explaining and exploring ecosystem properties and changes in community structure driven by biotic and abiotic factors. In this paper, we review the application of eco-exergy for the assessment of ecosystem health and development of structurally dynamic models (SDMs). The limitations and possible future applications of the approach are also addressed.     

Treibhausgas-Emissionen zukünftiger Erdgas-Bereitstellung für Deutschland

Background

Natural gas makes a significant contribution to the current energy supply and its importance, in relation to both the German and worldwide energy supplies, will increase further in decades to come. In addition to its high degree of efficiency, the low level of direct GHG combustion emissions is also an advantageous factor. However, around 90% of natural gas is methane (CH₄), which is the second most significant GHG due to its high greenhouse potential (21 times higher than CO₂). Therefore, high levels of direct gas losses of natural gas in its production, processing, transport and distribution could neutralise its low emission advantages. This is particularly apparent when considering the growing distances between production and use, the demanding production processes and the upcoming worldwide market for LNG (liquefied natural gas).

Aim

This paper aims to analyse and illustrate the future GHG emissions of the whole process chain of natural gas (indirect emissions) to be supplied to the German border over the next 2 decades. This should allow the comparison of total GHG emissions (indirect and direct) of natural gas with the GHG emissions of other fossil fuels. By considering likely changes in gas origin as well as dynamic changes in the infrastructure and technology of gas production, processing and transport until 2030, all relevant factors are included. The study focuses on the emissions of Russian natural gas as Russia is already, and will be in the future, the most important gas supplier to the German and European gas markets.

Results and Discussion

The analysis illustrates a significant change in the gas supply over the next two decades. The EU Gas Fields are in decline and it is predicted that these will run dry. In parallel the share of Russian and Norwegian natural gas, and also the levels of LNG production (e.g. from Algeria or Egypt), will increase. Although the potential for GHG emissions tends to grow as a result of greater transport distances and demanding production and processing activities, high investment in necessary mitigation options (e.g. through replacing older and inefficient technology; updating to state-of-the-art technology) may neutralise the increase. The overall result of these counteracting trends will be to decrease GHG emissions, in a range of around 12% per TJ of direct emissions of natural gas, depending on the level of investment in the modernisation of the Russian gas infrastructure and the improvements of the LNG process. In the two given scenarios the indirect emissions of the natural gas used in Germany will decrease from about 23 million t CO₂-eq (2005) to 19.5 or 17.6 million t CO₂-eq in the year 2030. In spite of a significant higher gas consumption the emissions are reduced in the first scenario due to technical modifications. In the second scenario the emission reduction is based on the lower gas consumption.

Conclusions

At present, the indirect GHG emissions of the natural gas process chain are comparable to the indirect emissions produced by oil and coal. The emission trend of the natural gas process chain will markedly decrease if the mitigation options are followed consistently. However, in order to ensure the long-term security of natural gas supply for future decades, a high level of investment is essential. With regard to future emissions, the best available technology and, therefore, that which is most economically feasible in the long term, should be used. Under these conditions natural gas — as the fossil fuel with the lowest levels of GHG emissions — can play a major role in the transition to a renewable energy supply for the future.     

Simulating future land use and ecosystem services in Northern Thailand

Enhancing ecosystem services is important as it provides foundation for the wellbeing of people. This paper presents the future land use simulation for enhancing ecosystem services using CLUMondo dynamic spatial model. The land use change was assessed from 1989 to 2013 in Wang Thong watershed of Northern Thailand using GIS and a set of ecosystem services was assessed using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. Future land uses until 2030 were projected for three policy scenarios, namely business-as-usual, integrated land use development, and enhancing environmental services with different levels of emphasis on ecosystem services. In business-as-usual scenario, it was observed that ecosystem services will decline by 2030 from the base year of 2013, whereas in integrated land use development scenario, the ecosystem services will increase by 5% compared to base year due to anticipated effective protection of remaining forests in all existing and proposed protected areas of the study area. In enhancing environmental services scenario, the ecosystem services will increase by 15%. Such results can serve as useful information in policy formulation in developing land use options, which help enhance ecosystem services in future.     

A dynamic programming implemented resource competition game theoretic model

Resource competition is commonly occurred in animal populations and studied intensively by researchers. Previous studies have applied game theoretic model by finding Nash equilibrium to investigate this phenomenon. However computation of the Nash equilibrium requires an understanding of the payoff matrix that allocates the rewards received by players when they adopt each of the strategies in the game. In our study we present a dynamic programming implemented framework to compute 2 × 2 intraspecific finite resource allocation game's payoff matrix explicitly. We assume that two distinct types of individuals, aggressive and non-aggressive, are in the population. Then we divide the entire animal development period into three different stages: initialization, quasilinear growth and termination. Each stage for each type of players is specified with their own development coefficient, which determines how resource consumption could convert into strength as reward. Each player has equal and finite resource at the beginning of their development and fights against other players in the population to maximize its own potential reward. Based on these assumptions it is reasonable to use backward induction dynamic programming to compute payoff matrix. We present numerical examples for three different types of aggressive individuals and compute the payoff matrices correspondingly. Then we use the derived payoff matrices to determine the Nash equilibrium and Evolutionary Stable Strategy. Our research provide a framework for future quantitative studies on animal resource competition problems and could be expanded to n-players interspecific stochastic asymmetric resource allocation problem by changing some settings of dynamic programming formulation.     

Phytoplankton production modelling in three marine ecosystems—static versus dynamic approach

Phytoplankton productivity is usually determined from water samples incubated at a number of irradiance levels during several hours. The resultant productivity-irradiance (P–E) curves are then used to estimate local and/or global phytoplankton production. However, there is growing evidence that these curves, referred as static, underestimate phytoplankton photosynthesis to a great deal, by assuming a stable response to light over the incubation period. One of the drawbacks of static P–E curves is the overestimation of photoinhibition.In this work, three one-dimensional vertically resolved models were developed as simply as possible, to investigate differences between static and dynamic phytoplankton productivity in three marine ecosystems: a turbid estuary, a coastal area and an open ocean ecosystem. The results show that, when photoinhibition development time is considered (dynamic model), the primary production estimates are always higher than when calculated with the static model. The quantitative importance of these differences varies with the type of ecosystem and it appears to be more important in coastal areas and estuaries (from 21 to 72%) than in oceanic waters (10%). Thus, these results suggest that primary production estimates, obtained under the assumption of a static behaviour response to light, may underestimate the real values of global phytoplankton primary production. Calculations suggest that the quantitative importance of this underestimation may be larger than the global missing carbon sink.     

Environmental-economic models for total emission control of regional environmental pollution — input-output approach

This paper deals with a Leontief-type dynamic input-output analysis for total emission control of pollution. A dynamic input-output model can be described as a linear programming problem. In this paper an objective function to be minimized is chosen as the sum of pollutants emitted in a regional area throughout the planning period. It is assumed that consumption grows with a constant growth rate throughout the planning period. With this model, we can tell how to assign the elimination rate of pollutants to each production sector, under the constraint that the total emission standard is satisfied in each term of the planning period.     

Forecasting industrial emissions: a monetary approach vs. a physical approach

Forecasts of industrial emissions provide a basis for impact assessment and development planning. To date, most studies have assumed that industrial emissions are simply coupled to production value at a given stage of technical progress. It has been argued that the monetary method tends to overestimate pollution loads because it is highly influenced by market prices and fails to address spatial development schemes. This article develops a land use-based environmental performance index (L-EPI) that treats the industrial land areas as a dependent variable for pollution emissions. The basic assumption of the method is that at a planning level, industrial land use change can represent the change in industrial structure and production yield. This physical metric provides a connection between the state-of-the-art and potential impacts of future development and thus avoids the intrinsic pitfalls of the industrial Gross Domestic Product-based approach. Both methods were applied to examine future industrial emissions at the planning area of Dalian Municipality, North-west China, under a development scheme provided by the urban master plan. The results suggested that the LEPI method is highly reliable and applicable for the estimation and explanation of the spatial variation associated with industrial emissions.     

Detection of current and potential hazelnut plantation areas in Trabzon, North East Turkey using GIS and RS

Monitoring agricultural products requires the periodic determination of land cover and the production of land use policies in an optimum way. The hazelnut is one of the important Turkish agricultural exports and Turkey provides 77% of the world's hazelnuts. In Turkey, hazelnut production exceeds the demand; new regulations have been enacted to create new land use policies. By putting into practice regulations restricting hazelnut plantation areas, a more efficient and productive hazelnut harvest policy could be created. Therefore, more information on existing land cover is required to determine optimum (or ideal) potential hazelnut areas (PHA) and to forecast future crop production. The principle aim of this study is to create a methodology for determining existing PHA, using Geographic information system (GIS) and remote sensing (RS) techniques regarding to support hazelnut policy developers and economists. This study was basically carried out in the province of Trabzon, which is one of the most important hazelnut production areas in Turkey. Landsat ETM+ image was used to generate a current land cover classification. Using the supervised classification method, overall accuracy was determined to be 84.7%. Suitable hazelnut areas were determined according to criteria settled by government regulations.     

Conservation decision-making in large state spaces

When looking for the best course of management decisions to efficiently conserve metapopulation systems, a classic approach in the ecology literature is to model the optimisation problem as a Markov decision process and find an optimal control policy using exact stochastic dynamic programming techniques. Stochastic dynamic programming is an iterative procedure that seeks to optimise a value function at each timestep by evaluating the benefits of each of the actions in each state of the system defined in the Markov decision process.Although stochastic dynamic programming methods provide an optimal solution to conservation management questions in a stochastic world, their applicability in metapopulation problems has always been limited by the so-called curse of dimensionality. The curse of dimensionality is the problem that adding new state variables inevitably results in much larger (often exponential) increases in the size of the state space, which can make solving superficially small problems impossible. The high computational requirements of stochastic dynamic programming methods mean that only simple metapopulation management problems can be analysed. In this paper we overcome the complexity burden of exact stochastic dynamic programming methods and present the benefits of an on-line sparse sampling algorithm proposed by Kearns, Mansour and Ng (2002). The algorithm is particularly attractive for problems with large state spaces as the running time is independent of the size of the state space of the problem. This appealing improvement is achieved at a cost: the solutions found are no longer guaranteed to be optimal.We apply the algorithm of Kearns et al. (2002) to a hypothetical fish metapopulation problem where the management objective is to maximise the number of occupied patches over the management time horizon. Our model has multiple management options to combat the threats of water abstraction and waterhole sedimentation. We compare the performance of the optimal solution to the results of the on-line sparse sampling algorithm for a simple 3-waterhole case. We find that three look-ahead steps minimises the error between the optimal solution and the approximation algorithm. This paper introduces a new algorithm to conservation management that provides a way to avoid the effects of the curse of dimensionality. The work has the potential to allow us to approximate solutions to much more complex metapopulation management problems in the future.     

Reducing environmental impacts through socioeconomic transitions: critical review and prospects

● Reducing environmental impacts through socioeconomic structural transitions. ● Simulation of looping the dynamic material cycle should be concerned. ● Transboundary effects of socioeconomic transitions need to be analyzed. ● Facilitating interregional cooperation and synergetic control mechanisms. Rapid socioeconomic development has caused numerous environmental impacts. Human production and consumption activities are the underlying drivers of resource uses, environmental emissions, and associated environmental impacts (e.g., ecosystem quality and human health). Reducing environmental impacts requires an understanding of the complex interactions between socioeconomic system and environmental system. Existing studies have explored the relationships among human society, economic system, and environmental system. However, it is unclear about the research progress in the effects of socioeconomic activities on environmental impacts and the potential directions of future research. This critical review finds that existing studies have identified critical regions, sectors, and transmission pathways for resource uses, environmental emissions, and environmental impacts from supply chain perspectives. Moreover, scholars have characterized the impacts of socioeconomic transitions on resource uses and environmental emissions. However, existing studies overlook the dynamic nature of the interconnections among human society, economic system, and environmental system. In addition, the effects of socioeconomic structural transitions on environmental impacts remain unknown. This review proposes four prospects and possible solutions that will contribute to a better understanding of the complex interactions among human society, economic system, and environmental system. They can help identify more effective solutions to reduce environmental impacts through socioeconomic transitions.     

Testing the generalization of artificial neural networks with cross-validation and independent-validation in modelling rice tillering dynamics

Neural networks (NN) rely on the inner structure of available data sets rather than on comprehension of the modeled processes between inputs and outputs. Therefore, neural networks have been regarded as highly empirical models with limited extrapolation capability to situations outside the range of the training and validation data sets. In this study, the generalization ability of neural networks in predicting rice tillering dynamics was tested and several techniques inducing the generalization ability of neural networks were compared. We compared the performance of cross-validated neural networks with independent-validated neural networks and found that neural networks were able to extrapolate and predict tillering dynamics if the data were within the range of inputs of the training set. An inadequate training set resulted in overfitting of available data and neural networks that were not generalizable. The training set size required to enable a neural network to generalize and predict rice tillering dynamics was found to be at least 9 times as many training patterns for each weight. When a large number of variables are included in the input vector of a neural network with inadequate amounts of training data, we strongly recommend that the dimension of the input vector is reduced using principle component analysis (PCA), correspondence analysis (CA) or similar techniques to decrease the number of weights before the training procedure to improve the generalization ability of the NN. If the amount of training data still is not sufficient after the dimension of the input vector is reduced, regularization techniques, such as early stopping, jittering, and especially the embedment of estimated results by a theoretical model into the training set, should be used to improve the generalization ability of the neural network. The generalization of neural networks presents a wide spectrum of problems, and the proposed approaches are not confined strictly to modelling rice tillering dynamics but can be applied to other agricultural and ecological systems.