Cybersecurity and dynamic operation in practice: Equipment impacts and safety guarantees

Though dynamic operation of chemical processes has been extensively explored theoretically in contexts such as economic model predictive control or even considering the potential for cyberattacks on control systems creating non-standard operating policies, important practical questions remain regarding dynamic operation. In this work, we look at two of these with particular relevance to process safety: (1) evaluating dynamic operating policies with respect to process equipment fidelity and (2) evaluating procedures for determining the parameters of an advanced control law that can promote both dynamic operation as well as safety if appropriately designed. Regarding the first topic, we utilize computational fluid dynamics and finite element analysis simulations to analyze how cyberattacks on control systems could impact a metric for stress in equipment (maximum Von Mises stress) over time. Subsequently, we develop reduced-order models showing how both a process variable and maximum Von Mises stress vary over time in response to temperature variations at the boundary of the equipment, to use in evaluating how advanced control frameworks might impact and consider the stress. We close by investigating options for obtaining parameters of an economic model predictive control design that would need to meet a variety of theoretical requirements for safety guarantees to hold. This provides insights on practical safety aspects of control theory, and also indicates relationships between control and design from a safety perspective that highlight further relationships between design and control under dynamic operation to deepen perspectives from the computational fluid dynamics and finite element analysis discussions.     

基于缓冲区重采样的LSTM林火预测模型*

为提高林火风险预测精度,挖掘地图上隐含的空间信息、时间序列上隐含的长期趋势和循环波动,提出1种基于缓冲区重采样的长短期记忆（LSTM）林火预测模型,选取15个与林火相关的影响因素,以方差膨胀因子为评价指标对其进行多重共线性检验,方差膨胀因子大于10的因素具有共线性,并采用信息增益率验证筛选结果的合理性。考虑到火灾的空间聚集特性,采用缓冲区分析与过采样相结合方法减少样本不均衡现象的影响,最终得到176 732条样本。对12个影响因素和研究时间段的火点建立LSTM预测模型,对森林火灾发生风险进行预测。研究结果表明:基于缓冲区重采样的LSTM林火预测模型有效考虑时空上隐含的信息,预测模型准确率为87.06%,特异性为97.99%,敏感度为76.12%,阳性预测率为97.43%,阴性预测率为80.41%,ROC曲线与AUC值均优于随机森林（RF）和支持向量机（SVM）这2种基准算法。维尔克松秩和检验发现,本文提出的模型与基准算法结果具有显著性差异。研究结果可为提高林火风险预测精度提供参考。     

Importance of information on tillage practices in the modelling of environmental processes and in the use of environmental indicators

Tillage has been and will always be integral to crop production. Tillage can result in the degradation of soil, water, and air quality. Of all farm management practices, tillage may have the greatest impact on the environment. A wide variety of tillage equipment, practices and systems are available to farmers, providing opportunities to enhance environmental performance. These opportunities have made tillage a popular focus of environmental policies and programs such as environmental indicators for agriculture. This paper provides a very brief examination of the role of tillage in crop production, its effect on biophysical processes and, therefore, its impact on the environment. Models of biophysical processes are briefly examined to demonstrate the importance of tillage relative to other farm management practices and to demonstrate the detail of tillage data that these models can demand. The focus of this paper is an examination of the use of information on tillage in Canada's agri-environmental indicators initiative, National Agri-environmental Health Analysis and Reporting Program (NAHARP). Information on tillage is required for several of the indicators in NAHARP. The type of data used, its source, and its quality are discussed. Recommendations regarding the collection of tillage data and use of tillage information are presented.     

Sampling and Mapping a Soil Erosion Cover Factor by Integrating Stratification,Model Updating and Cokriging with Images

Cost-efficient sample designs for collection of ground data and accurate mapping of variables are required to monitor natural resources and environmental and ecological systems. In this study, a sample design and mapping method was developed by integrating stratification, model updating, and cokriging with Landsat Thematic Mapper (TM) imagery. This method is based on the spatial autocorrelation of variables and the spatial cross-correlation among them. It can lead to sample designs with variable grid spacing, where sampling distances between plots vary depending on spatial variability of the variables from location to location. This has potential cost-efficiencies in terms of sample design and mapping. This method is also applicable for mapping in the case in which no ground data can be collected in some parts of a study area because of the high cost. The method was validated in a case study in which a ground and vegetation cover factor was sampled and mapped for monitoring soil erosion. The results showed that when the sample obtained with three strata using the developed method was used for sampling and mapping the cover factor, the sampling cost was greatly decreased, although the error of the map was slightly increased compared to that without stratification; that is, the sample cost-efficiency quantified by the product of cost and error was greatly increased. The increase of cost-efficiency was more obvious when the cover factor values of the plots within the no-significant-change stratum were updated by a model developed using the previous observations instead of remeasuring them in the field.     

Assessment of the Water Quality and Ecosystem Health of the Great Barrier Reef (Australia): Conceptual Models

Run-off containing increased concentrations of sediment, nutrients, and pesticides from land-based anthropogenic activities is a significant influence on water quality and the ecologic conditions of nearshore areas of the Great Barrier Reef World Heritage Area, Australia. The potential and actual impacts of increased pollutant concentrations range from bioaccumulation of contaminants and decreased photosynthetic capacity to major shifts in community structure and health of mangrove, coral reef, and seagrass ecosystems. A detailed conceptual model underpins and illustrates the links between the main anthropogenic pressures or threats (dry-land cattle grazing and intensive sugar cane cropping) and the production of key contaminants or stressors of Great Barrier Reef water quality. The conceptual model also includes longer-term threats to Great Barrier Reef water quality and ecosystem health, such as global climate change, that will potentially confound direct model interrelationships. The model recognises that system-specific attributes, such as monsoonal wind direction, rainfall intensity, and flood plume residence times, will act as system filters to modify the effects of any water-quality system stressor. The model also summarises key ecosystem responses in ecosystem health that can be monitored through indicators at catchment, riverine, and marine scales. Selected indicators include riverine and marine water quality, inshore coral reef and seagrass status, and biota pollutant burdens. These indicators have been adopted as components of a long-term monitoring program to enable assessment of the effectiveness of change in catchment-management practices in improving Great Barrier Reef (and adjacent catchment) water quality under the Queensland and Australian Governments’ Reef Water Quality Protection Plan.     

Linking Models of Land Use,Resources, and Economy to Simulate the Development of Mountain Regions (ALPSCAPE)

We present a framework of a scenario-based model that simulates the development of the municipality of Davos (Swiss Alps). We illustrate our method with the calculation of the scenario for 2050 “Decrease in subsidies for mountain agriculture and liberalization of markets.” The main objective was to link submodels of land-use allocation (regression-based approach), material and energy flows submodels (Material and Energy Flux Analysis), and economic submodels (Input–Output Analysis). Letting qualitative and quantitative information flow from one submodel to the next, following the storyline describing a scenario, has proven to be suitable for linking submodels. The succession of the submodels is then strongly dependent on the scenario. Qualitative information flows are simulated with microsimulations of actor choices. Links between the submodels show different degrees of robustness: although the links involving microsimulations are the weakest, the uncertainty introduced by the land-use allocation model is actually advantageous because it allows one possible change in the landscape in the future to be simulated. The modeling results for the scenario here presented show that the disappearance of agriculture only marginally affects the region’s factor income, but that the consequences for the self-sufficiency rate, for various landscape-related indicators and ecosystem services, and for the economy in the long term may be considerable. These benefits compensate for agriculture’s modest direct economic value. The framework presented can potentially be applied to any region and scenario. This framework provides a basis for a learning package that allows potential detrimental consequences of regional development to be anticipated at an early stage.     

福建省生产废水和生活污水污染物排放的驱动力及其时空分异

采用对数平均迪氏指数方法,区分生产和生活两个体系,构建时空分解分析模型,追踪了福建省9个设区市2011—2019年水污染物排放变化的关键驱动力及其贡献的时空差异.结果显示：研究期内福建省工业废水污染物排放持续减少,并且各驱动力贡献的区域差距明显变小,趋于平衡;生活污水污染物排放量仍保持高位,各驱动力贡献的区域差距基本保持不变.其中,经济规模扩张是福建省水污染物排放的主导驱动力,主要源于福州、厦门、泉州经济赶超发展影响;城镇化发展对区域生活污水污染物排放的驱动影响表现为增排效应,以福州和厦门尤为显著;工业化发展对区域工业废水污染物排放的影响效应由正驱动逐渐转变为负驱动,这主要归功于三明和泉州产业结构调整优化的拉动 效应;技术效应一直是福建省水污染物排放控制的重要驱动力,但部分地区已逐渐步入生活污染物技术减排攻坚期.     

随机价格下杉木人工林的碳汇收益及最优轮伐期确定

发展林业碳汇是应对全球气候变化及实现中国2060年碳中和的重要举措。基于改进的Faustmann-Hartman模型,以中国南方浙江、福建和江西三个省份杉木人工林为研究对象,使用时间序列模型拟合并预测中国碳排放权交易市场的碳汇价格,通过蒙特卡洛模拟确定最优轮伐期及碳汇收益。研究结果表明：（1）依次纳入木材收益、地上生物量碳汇收益和死亡有机质碳汇收益时,杉木人工林的最优轮伐期分别为21.85年、22.98年和22.88年;（2）上述三种情景下,林地期望价值的净现值分别为20408.20元/hm²、24587.29元/hm²和28101.11元/hm²;（3）全面考虑包含死亡有机质碳库在内的林业碳汇效益,能够稳定提高林地所有者收益约7.02%~21.61%。此外,应进一步考虑多轮伐期下税收政策及自然风险等因素对碳汇营林的影响,这是确定最优轮伐期和碳汇收益后续研究值得重视的问题。     

森林保险支付意愿及影响因素分析——基于异质性营林主体视角

基于期望效用函数理论分析了异质性营林主体的森林保险支付意愿及差异,并以传统小林农和新型林业经营主体为研究对象,以福建省382户传统小林农和88户新型林业经营主体的调研数据为基础,综合运用条件估值法、卡方检验及Cox比例风险模型,对异质性营林主体的森林保险支付意愿与差异及支付意愿影响因素进行对比与分析。研究表明：传统小林农和新型林业经营主体的森林保险意愿支付水平存在显著差异,在1000~2500元/亩保障水平下,传统小林农的意愿支付水平分别为1.911元/亩、2.941元/亩、3.532元/亩及3.979元/亩,新型林业经营主体为1.632元/亩、3.971元/亩、5.809元/亩及6.864元/亩;两类营林主体的支付意愿均随保额的提高而提高,但新型林业经营主体的提升幅度远高于小林农。异质性营林主体的森林保险支付意愿影响因素也存在明显差别,这与其在森林保险认知特征、林业生产经营特征、林业灾损特征、森林保险产品评价特征等方面存在显著差异有关。此外,林地面积对两类营林主体支付意愿均具有显著影响,规模化、集约化的林业生产经营可促进林业经营主体的森林保险愿意支付水平。