Development of marginal emission factors for N losses from agricultural soils with the DNDC–CAPRI meta-model

The article discusses marginal emission factors for N losses from agricultural soils, with rape and wheat as examples, and presents results for EU15 as high-resolution maps and aggregated to Member State level. The results are generated by linking the economic model for the agricultural sector CAPRI (Common Agricultural Policy Regional Impact) with spatial down-scaling, and a statistical meta-model for the bio-physical model DNDC (DeNitrification–DeComposition). For a given agro-economic scenario, CAPRI supplies for each crop the crop share, yield and fertilizer application rate spatially downscaled to clusters of 1 km × 1 km grid cells. The results from CAPRI are processed by a meta-model of DNDC to estimate the local greenhouse gas emissions from the soil. DNDC is a dynamic process-oriented model, which estimates trace gas fluxes and nutrient turnover in agricultural soils. The fit of the regressions is typically very good (0.95R² for the majority of the regressions), and all coefficients are significant at 99% probability. The meta-model allows a seamless integration between the economic and the bio-physical models, offering additional benefit such as the site-specific calibration of the bio-physical model ensuring the match between simulated and observed yield at the grid-level.The meta-model is used to calculate marginal emission factors for a 1 kg ha⁻¹ increase of mineral N and manure fertilizer rates for rape and wheat, at different levels of fertilization. They show that for Western European farming practice, only a small fraction of extra nitrogen fertilizer would go into increased yields: most of it would be emitted to the environment. The largest spatial variability is observed for N₂O emissions. The derivation of marginal emission factors is just one of the many possible uses for the linked regionalized agro-economic and soil chemistry model, which exploits to a large extent both geo-referenced and regionally available statistical information at European scale.     

Safety analysis and risk assessment of a Micro-GtL Plant

Laboratory hydrogen generators, medical oxygen, and micro-breweries are examples of modular and micro technologies that are commercial successes. Researchers, patients, and unskilled workers operate these facilities but more complex processes require highly qualified personnel to ensure they operate safely. Modular-micro processes in isolated locations meet economic objectives when operated remotely thereby minimizing labor costs. Mitigating the risk requires a comprehensive hazards analysis with advanced control systems particularly for explosive and toxic compounds. Here, we propose a method called Failure Mode Risk Decision (FMRD) to review the inherent hazards of a micro-refinery unit (MRU) that converts flared and wasted natural gas to long chain hydrocarbons. This approach combines the Process Flow Failure Mode (PFFM) methodology as a systematic and reliable technique with a novel numerical risk assessment to improve the analytical evaluation of hazardous conditions. The objective is to combine causes and consequences in a single metric, where scaled probability of evident causes and severity of consequences are used to derive a risk level measure. With the proposed metric, the magnitude of a potential hazard is directly correlated with the risk level. This mechanism identifies extra risk scenarios compared to the classical hazard analysis method and provides a straightforward comprehensive numerical assessment to represent the inherent and residual risks to facilitate justifying the hazardous scenarios. Accordingly, we design a safety loop and supply all the required facilities to remove the potential risks at the process plant. Not only the proposed methodology clarifies the risks of the MRU presented in this study, but can be extended to review the hazards of other chemical process plants.     

Modeling soil and plant phosphorus within DSSAT

The crop models in the Decision Support System for Agrotechnology Transfer (DSSAT) have served worldwide as a research tool for improving predictions of relationships between soil and plant nitrogen (N) and crop yield. However, without a phosphorus (P) simulation option, the applicability of the DSSAT crop models in P-deficient environments is limited. In this study, a soil-plant P model integrated to DSSAT was described, and results showing the ability of the model to mimic wide differences in maize responses to P in Ghana are presented as preliminary attempts to testing the model on highly weathered soils. The model simulates P transformations between soil inorganic labile, active and stable pools and soil organic microbial and stable pools. Plant growth is limited by P between two concentration thresholds that are species-specific optimum and minimum concentrations of P defined at different stages of plant growth. Phosphorus stress factors are computed to reduce photosynthesis, dry matter accumulation and dry matter partitioning. Testing on two highly weathered soils from Ghana over a wide range of N and P fertilizer application rates indicated that the P model achieved good predictability skill at one site (Kpeve) with a final grain yield root mean squared error (RMSE) of 535 kg ha⁻¹and a final biomass RMSE of 507 kg ha⁻¹. At the other site (Wa), the RMSE was 474 kg ha⁻¹ for final grain yield and 1675 kg ha⁻¹ for final biomass. A local sensitivity analysis indicated that under P-limiting conditions and no P fertilizer application, crop biomass, grain yield, and P uptake could be increased by over 0.10% due to organic P mineralization resulting from a 1% increase in organic carbon. It was also shown that the modeling philosophy that makes P in a root-free zone unavailable to plants resulted in a better agreement of simulated crop biomass and grain yield with field measurements. Because the complex soil P chemistry makes the availability of P to plants extremely variable, testing under a wider range of agro-ecological conditions is needed to complement the initial evaluation presented here, and extend the use of the DSSAT-P model to other P-deficient environments.     

Mathematical problem definition for ecological restoration planning

Ecological restoration is an increasingly important tool for managing and improving highly degraded or altered environments. Faced with a large number of sites or ecosystems to restore, and a diverse array of restoration approaches, investments in ecological restoration must be prioritized. Nevertheless, there are relatively few examples of the systematic prioritization of restoration actions. The development of a general theory for ecological restoration that is sufficiently sophisticated and robust to account for the inherent complexity of restoration planning, and yet is flexible and adaptable to ensure applicability to a diverse array of restoration problems is needed. In this paper we draw on principles from systematic conservation planning to explicitly formulate the ‘restoration prioritization problem’. We develop a generalized theory for static and dynamic restoration planning problems, and illustrate how the basic problem formulation can be expanded to allow for many factors characteristic of restoration problems, including spatial dependencies, the possibility of restoration failure, and the choice of multiple restoration techniques. We illustrate the applicability of our generic problem definition by applying it to a case study - restoration prioritization on The Irvine Ranch Natural Landmark in Southern California. Through this case study we illustrate how the definition of the general restoration problem can be extended to account for the specific constraints and considerations of an on-the-ground restoration problem.     

基于PSR和云理论的农用地生态环境评价——以广东省新兴县为例

论文采用PSR框架构建评价指标体系,利用云理论分别构建定量指标与定性指标的云模型,对农用地生态环境进行评价。以广东省新兴县为例,得出新兴县农用地生态环境分值为0.75,农用地生态环境良好。并将云理论与模糊规则进行对比,得出新兴县农用地生态环境分值分别为0.75和0.70,两者结果差异不大,但是结果表明云理论能完整表达评价问题中的不确定性,避免模糊规则中隶属度函数确定繁琐的问题。     

Tools for an enhanced solvent properties screening in the early stages of pharmaceutical process development

The objective of this research was the implementation of tools for the evaluation of solvents trough property screening in the early stages of process development. An important feature of the tools is that the implementation of indexes, scores, or weights is avoided. Information already available from the literature was stored in a database in order to turn raw data into decision making information. As a result, a solvent radar chart, a solvent representation table, and a solvent telescopying tool were developed in an ASP.NET application. The synthesis of Propranolol was used as study case in order to explore the selection of solvents in the early stages of process development. The replacement of diethyl ether was possible in the extraction step, while solvent choices were detected for potential telescoping for extraction and crystallisation steps. Solubility was found as a critical parameter in telescoping analysis. The methodology proposed enhanced the view towards a more holistic perspective and a more robust solvent screening process. As a consequence, the next steps into solvent evaluation and process development can be reduced.     

安全管理决策支持系统及其最新进展

安全管理是企业管理的重要组成部分,是实现安全生产的有力保证.决策支持系统是实现安全管理定性与定量分析有机结合的有效手段.该文结合安全管理,简要阐述了决策支持系统产生的背景、内容和发展趋势.介绍了作者在企业安全管理决策支持系统研制方面的主要结果和进一步工作的构想.     

Choice of stakeholder groups and members in multicriteria decision models

Simplistic economic objectives such as maximisation of producer profits are of little relevance in generating information to assist in the management of natural resources beyond the individual firm level. To provide data and information to support decision-making in natural resource management, it is necessary to take into account the views of various stakeholder groups and the multiple objectives of each group, through the use of some form of multicriteria analysis (MCA). Important decisions arise in the choice of stakeholder, since this will influence the management advice generated. Many groups and individuals can be affected by resource management decisions, but it would be impractical to attempt to identify the objectives and estimate their importance for each group. Also, questions arise concerning whether or not to include government agencies (which represent the broader community) and researchers as stakeholders. A further issue concerns choosing representative samples of stakeholder groups, from which to obtain preference data. Discussions with modellers and a reading of the literature would suggest that the choice of stakeholder groups and representatives is conducted haphazardly and is perhaps biased, and that a more systematic approach is needed. This article explores the above issues with reference to a number of multicriteria analyses, including local studies.     

秦皇岛市环境规划决策支持系统初探

在分析传统的宏观和微观环境决策模型的基础上,着重探讨了宏观与微观环境决策模型的结合使用问题,并根据秦皇岛市的实际,分析了建立环境规划决策支持系统的基本框架以及该系统的主要功能。      

Joint operation rules considering the uncertainty of energy available for multiple cascaded hydropower system

Multi-reservoir operation rules have been widely used in practice operation. The operation rules are often derived from historical or simulated run-off information through implicit stochastic optimization or parameterization-simulation-optimization. The output decisions of operation rules are usually obtained without considering inflow forecasting or using perfect runoff forecast information, which is hardly implemented in practical applications. This paper proposes robust joint operation rules for multiple cascaded reservoirs considering the uncertainty of energy available. The rule parameters are optimized using multi-step genetic algorithm for minimum-power maximization. A case study for a three-cascaded-reservoirs system shows that, compared with deterministic joint operation rules, the accuracy of energy available estimation of joint operation rules is increased by 2.3%, considering inflow uncertainty. The simulated minimum-power decision of joint operation rules considering the uncertainty of energy available is 40.4% higher than that of determinate joint operation rules. Results indicate that there is a possibility of obtaining greater and more effective power decisions through the joint operation rules considering the uncertainty of available energy.