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Nitrate (N) leaching from intensively managed cropping systems is of environmental concern and it varies at local scale. To evaluate the performance of agricultural practices at this scale, there is a need to develop comprehensive assessments of N leaching and the N leaching reduction potential of mitigation measures. A model-based analysis was performed to (i) estimate N leaching from Danish cropping systems, representing 20 crop rotations, 3 soil types, 2 climates and 3–4 levels of manure (slurry)-to-fertilizer ratios, but with same available N (according to regulatory N fertilization norms), and (ii) appraise mitigation potential of on-farm measures (i.e. catch crops, early sowing of winter cereals) to reduce N leaching. The analysis was performed using a process-based agro-environmental model (Daisy). Simulated average N leaching over 24 years ranged from 16 to 85 kg N/ha/y for different crop rotations. Rotations with a higher proportion of spring crops were more prone to leaching than rotations having a higher proportion of winter cereals and semi-perennial grass-clover leys. N leaching decreased with increasing soil clay content under all conditions. The effect of two climates (different regions, mainly differing in precipitation) on N leaching was generally similar, with slight variation across rotations. Supplying a part of the available N as manure-N resulted in similar N leaching as mineral fertilizer N alone during the simulation period. Among the mitigation measures, both undersown and autumn sown catch crops were effective. Effectiveness of measures also depended on their place and frequency of occurrence in a rotation. Adopting catch crops during the most leaching-prone years and with higher frequency were effective choices. This analysis provided essential data-driven knowledge on N leaching risk, and potential of leaching reduction options. These results can serve as a supplementary guiding-tool for farmers to plan management practices, and for legislators to design farm-specific regulatory measures.

Soils perform several functions in delivering ecosystem services and soil thematic maps are useful for environmental modelling, landscape planning, and management optimization. This study aimed at producing the first soil rooting depth map of Italy at 1:250,000 scale based on the legacy soil maps, soil data and benchmark profiles, combined with the auxiliary data. The map highlights that moderately deep (33%) and deep (25%) soils are predominant and mainly distributed in hilly areas, while very deep soils (18%) are prevalent in the fluvial and coastal plains. The validation procedure showed that 87% of the soil rooting depth map classes fall within the same and adjacent classes of the measured soil profiles database. The soil rooting depth map of Italy at 1:250,000 scale can be a useful tool to support land management and spatial planning in terms of agro-environmental measures, making reliable assessments for ecological sustainability studies, and for environmental territorial analyses.

Geospatial information plays an important role in environmental modelling, resource management, business operations, and government policy. However, very little or no commonality between formats of various geospatial data has led to difficulties in utilizing the available geospatial information. These disparate data sources must be aggregated before further extraction and analysis may be performed. The objective of this paper is to develop a framework called PlaniSphere, which aggregates various geospatial datasets, synthesizes raw data, and allows for third party customizations of the software. PlaniSphere uses NASA World Wind to access remote data and map servers using Web Map Service (WMS) as the underlying protocol that supports service-oriented architecture (SOA). The results show that PlaniSphere can aggregate and parses files that reside in local storage and conforms to the following formats: GeoTIFF, ESRI shape files, and KML. Spatial data retrieved using WMS from the Internet can create geospatial data sets (map data) from multiple sources, regardless of who the data providers are. The plug-in function of this framework can be expanded for wider uses, such as aggregating and fusing geospatial data from different data sources, by providing customizations to serve future uses, which the capacity of the commercial ESRI ArcGIS software is limited to add libraries and tools due to its closed-source architectures and proprietary data structures. Analysis and increasing availability of geo-referenced data may provide an effective way to manage spatial information by using large-scale storage, multidimensional data management, and Online Analytical Processing (OLAP) capabilities in one system.

Spatiotemporal data mining has many important applications in environmental modelling. This paper introduces a modified algorithm for spatiotemporal data mining based on density-based spatial clustering of applications with noise (DBSCAN). Based on the modified algorithm, a geographic information system (GIS) add-in was developed using ArcObjects and C#, and is freely available for download. Compared with some existing methods, the new method can perform automated detection of spatiotemporal clusters using limited user input parameters. The application of the add-in was demonstrated using summer temperature data collected from 104 weather stations in southwest China from 1961 to 2011. The results suggest that the modified algorithm can provide more detailed partition of temperature zones compared with some existing methods.

Major threats to freshwater ecosystems in the Andean-Amazon region include agriculture, point and nonpoint source pollution, hydroelectric dams, oil extraction, mining and road building, yet little is known about the baseline values and current state of rivers and streams, or how expanding urban, industrial and agricultural activities could affect and change these freshwater ecosystems and their diversity. Therefore, there is a need to understand physicochemical parameters at the basin scale in many large river systems in the Andean-Amazon such as the Napo River, a world biodiversity hotspot. Establishing baselines for these parameters under less developed conditions will be impossible after development in the watersheds increases and hydroelectric projects reach completion. In addition to collecting data to fill in information gaps in geology, vegetation, disturbance, and other parameters that influence water quality, it is important to use existing data in the Napo to predict chemical parameters throughout the watershed to set a baseline from which deviations from development and climate change can be assessed and to guide data collection efforts. In this study, we provide the first basin-wide estimates of physicochemical parameters (pH, conductivity, dissolved oxygen and temperature) for the entire Napo River Basin using a recently developed geostatistical technique called top kriging. Basin-wide predictions aligned well with observed values and a model validation test showed a strong goodness-of-fit for parameter estimates. Furthermore, our predictions aligned well with observed values from independent datasets from the Napo Basin. These predictions could be useful in developing water quality reference baselines for the basin and for monitoring relative changes to parameters, assist in the identification of priority areas within the basin for management and conservation efforts, direct future research, and be applied in other data-scarce basins in remote regions worldwide.

The great degree of human development in recent centuries has generated an environmental problem: the spread of human activities through the landscape without sustainable planning. Currently, most natural areas of the planet that are protected for their natural resources have not been impacted by linear infrastructure. The landscape is one of the natural resources that is adversely affected by linear infrastructure. In this short essay, a methodological procedure is described that is easy to use and cost effective and allows for early stage environmental planning. The method uses environmental assessment maps in which weighted pixel values for landscape quality and visual fragility are predetermined. GIS techniques, such as accumulated costs and driving direction scripts, are used to calculate linear infrastructure routes that have the lowest environmental impact. The optimal path is generated by quantitatively calculating the impact of each map pixel along the route such that alternative routes can be selected prior to construction. This method is a powerful tool for environmental modelling focused on the avoidance of environmental impacts during the assessment phase of a project.

Clean energy for all, as listed in the United Nation’s SDG7, is a key component for sustainable environmental development. Therefore, it is imperative to uncover the environmental implications of alternative energy technologies. SustainableGAS project simulates different process chains for the substitution of natural gas with renewable energies in the German gas market. The project follows an interdisciplinary approach, taking into account techno-social and environmental variabilities. However, this research highlights the project results from the environmental perspective. So far, a detailed assessment of the environmental costs of alternative gas technologies with a focus on the process of energy transition has remained rare. Although such data constitute key inputs for decision-making, this study helps to bridge a substantial knowledge gap. Competing land-use systems are examined to secure central ecosystem services. To fulfill this obligation, an Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) serves as the modelling tool. InVEST assesses ecosystem services (ES) that are or may be affected by alternative bioenergy technologies. Spatially explicit model results include the water provisioning from the Water Yield Model (WYM), soil erosion and sedimentation described by the Sediment Delivery Ratio (SDR), and nutrient fluxes (N) in response to changing land use are obtained through the Nutrient Delivery Ratio (NDR). The detailed model results are finally extrapolated, which provides a comprehensive image of the environmental impacts associated with bioenergy expansion in Germany from our combination of unique Renewable Gas Plants (RGPs). The final result shows that nutrient load will reduce in southern Germany by the year 2050 compared to the reference state, and biomass use reduced by 46% crops.

International audience; Pedometrics, the application of mathematical and statistical methods to the study of the distribution and genesis of soils, has broadened its scope over the past two decades. The primary focus of pedometricians has traditionally been on spatial and spatio-temporal soil inventories with numerical soil classification, geostatistical modelling of spatial variation and mapping. The rapid development of remote and proximal soil sensing as well as data-driven statistical modelling techniques have had a major impact on pedometrics over the past decades. During this time, a general demand for quantitative digital soil information for environmental modelling and management has compelled pedometricians to address other soil-related questions from a quantitative point of view: soil genesis and utility and quality of soil. While scientific progress is largely an autonomous process that is difficult to steer, research efforts could benefit from an agenda with pressing pedometric research topics. This paper defines and discusses ten recent or longstanding pedometrics challenges, with the attempt to identify knowledge gaps and suggest new concepts and methods to overcome them. The ten challenges were selected through a collaborative effort and may serve as a guidance for future pedometrics research and to foster collaboration among soil scientists. The challenges discussed in this paper are also indicators of the current understanding and state of knowledge from which progress can be measured in the future.

The first stage in the Precision Agriculture (PA) cycle entails data acquisition. This chapter deals with sensors used in conjunction with ground robotic platforms or terrestrial service units involved in scouting operations to model crops and their surrounding environment in PA and in Precision Fructiculture. In the following sections, various sensors and techniques used on ground robotic platforms and for geometric and structural modelling of crops and their environment are presented. A subsequent stage in the PA cycle covers data processing and information extraction to support farmers in taking management decisions. Sensor data and derived information can be used both for navigation in service units and for acquiring, featuring and classifying agricultural scenes. A description of the most used sensors, their functioning principles and processing techniques is provided, as well as real applications in case studies.

Serious games are increasingly developed and applied in environmental management as tools to collaboratively explore complexity. Yet, the research, design and implementation of serious games is still largely driven by technical aspects as a result of advances in computational power and in the gaming industry. Less attention has been given to research the extent to which the design of serious games can cater to the needs and desires of stakeholders with diverse backgrounds. The aim of this thesis is therefore to explore how a human centered design of serious games contributes to foster exploring complexity, facilitating stakeholder participation and stimulating social learning in environmental management. In this thesis, the design, application and evaluation of the Virtual River Game is described. First, the scope and background of the game was researched by conducting interviews with various stakeholders to gain an understanding of Dutch river management challenges and stakeholder perspectives on these. Second, the state-of-the-art in evaluating social learning outcomes of serious games to collaboratively explore complexity was analyzed and used as both design guidelines and an assessment framework for the game. Third, a novel, hybrid interface design was developed that, based on tangible interaction, has a physical game board with a bidirectional link to computer models that are widely used in practice. Fourth, the final prototype of the Virtual River Game was played in five sessions with both domain experts (river management professionals) and non-experts (non-professionals and laymen) to evaluate to what extent the game: (1) enables these stakeholders with diverse backgrounds to collaboratively explore river management complexity; and (2) stimulates social learning. The four main contributions of this thesis are: (1) applying a human centered design process to the design of serious games; (2) developing a novel interface design that uses a physical game board linked to environmental computer models to make the models accessible and transparent; (3) adding the ability to experiment with the design of management interventions as a game mechanic over selecting predefined interventions; and (4) creating the interface design as a platform to customize existing or develop new serious games with a spatial component.

The scope of this book does not allow all related subsurface environmental engineering applications to be covered in as much detail as in the topics of the previous sections. Yet, many fields and problems remain where, on the one hand, flow and transport processes play a dominant role and, on the other hand, enormous societal implications are inherent. Just a few are briefly touched upon below. While all the modelling-related parts of this book can be directly transferred and applied, we do not elaborate on hydrocarbon (oil and gas) production. The latter is already covered in many textbooks and, although it affects the environment immensely, it is not usually considered an environmental engineering topic. In fact, environmental engineering related to subsurface flow and transport problems has enormously benefited from the petroleum industry that has greatly contributed to the modelling concepts we apply today. This holds true particularly for the modelling of contaminated soils.

Modelling activities in science are not limited to the scientific community itself, but relate to and impact other domains of society. With this chapter, we conceptually explore matters of modelling at the science-policy interface. Understanding scientific modelling as a tool and school to provide evidenced-based knowledge, there are several particularities when modelling enters the sphere of policy-making and public debate.

International audience; There is growing interest in the application of the latest trends in computing and data science methods to improve environmental science. However we found the penetration of best practice from computing domains such as software engineering and cloud computing into supporting every day environmental science to be poor. We take from this work a real need to re-evaluate the complexity of software tools and bring these to the right level of abstraction for environmental scientists to be able to leverage the latest developments in computing. In the Models in the Cloud project, we look at the role of model driven engineering, software frameworks and cloud computing in achieving this abstraction. As a case study we deployed a complex weather model to the cloud and developed a collaborative notebook interface for orchestrating the deployment and analysis of results. We navigate relatively poor support for complex high performance computing in the cloud to develop abstractions from complexity in cloud deployment and model configuration. We found great potential in cloud computing to transform science by enabling models to leverage elastic, flexible computing infrastructure and support new ways to deliver collaborative and open science.

PRICE is an acronym for PRocess Industries in the Circular Economy. The main objective of the project is to prepare the collaborating industrial partners to the circular economy. This competence building project gathers industrial partners, research institutes, and the two largest universities in Norway. The participants are: Boliden Odda, Glencore Nikkelverk, KA Rasmussen, NOAH, Solberg Industri, Yara International, SINTEF industry, University of Oslo, and the Norwegian University of Science and Technology (NTNU). To reach this ambitious goal, there are sub-objectives: increased recirculation and recovery of metals and minerals—in general and between the participants in PRICE; understanding the behaviour (speciation) of and recovery or removal of valuable elements and toxic components present at low concentrations in process solutions; use of electrochemical means to enhance separation of elements present in trace concentrations; and assessment to evaluate the impacts of circular economy value-chains through environmental modelling (LCA) and techno/economic optimization.

Bayesian Networks (BNs) are an increasingly popular method for modelling environmental systems. The discretization of continuous variables is often required to use BNs. There are three main methods of discretization; manual, unsupervised, and supervised. Here, we compare and demonstrate each approach with a BN that predicts coastal erosion. Results reveal that supervised discretization methods produced BNs of the highest average predictive skill (73.8%), followed by manual discretization (69.0%) and unsupervised discretization (64.8%). However, each method has specific advantages that may make them more suitable for particular applications. Manual methods can produce physical meaningful BNs, which is favorable in environmental modelling. Supervised methods can autonomously and optimally discretize variables and may be preferred when predictive skill is a modelling priority. Unsupervised methods are computationally simple and versatile. The optimal discretization scheme should consider both the performance and practicality of the scheme.

This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy.

As a large archipelago with significant geographical variation and economic diversity, Indonesia requires detailed regional information when subjected to economic modelling. While such information is available, it however has not been integrated and harmonised into a comprehensive input–output database, thus preventing economic, social, and environmental modelling for investigating sub-national regional policy questions. We present the new IndoLab, a collaborative research platform for Indonesia, enabling input–output modelling of economic, social, and environmental issues in a cloud-computing environment. Within the IndoLab researchers are for the first time able to generate a time series of regionally and sectorally detailed and comprehensive, sub-national multi-region input–output (MRIO) tables for Indonesia. By integrating a multitude of economic, social, and environmental data into a single standardised processing pipeline and harmonised data repository, the IndoLab is able to generate MRIO t...

This study investigates the use of an evaluation model able to estimate the possibilities of reducing energy consumption and emissions of the building sector exploiting renewable energy sources. Specific attention is given to the use of ground source heat pumps in the urban context, proposing an ex-ante evaluation of different scenarios to identify the most balanced one in terms of energy, economic and environmental effects. The model is applied to a case study in Northern Italy to show how it can be used to support local administrations in energy urban planning, fitting economically and environmentally sustainable technologies. Moreover, it defines new boundaries in which the energy and environmental analyses should be carried out (spatial relocation), and the time span over which impacts have to be evaluated (temporal relocation).

Environmental archaeological enquiry has a long and vibrant history. Many of the same questions have persisted in archaeological dialogues over the past century. In particular, the effects of environmental change on demographic patterns, health, and societal stability are among the most pervasive questions being addressed by anthropological research. These studies have limitations, however. For example, evaluations of the complex relationships between environmental variables and human responses are only just beginning to emerge in anthropological literature. This goal requires high-resolution paleoclimate datasets and the use of quantitative modelling rooted in evolutionary and complex systems theory. This paper serves as a broad review of advances in environmental archaeological enquiry associated with environmental change and human response. I argue that the future of archaeological questions concerning human-environmental connection requires a re-evaluation of causality and the incorporation of complex systems approaches to address human responses to external pressures.

Anthropogenic land use is a major contributing factor to global environmental change, including forest cover loss and fragmentation. Land managers need up to date spatio-temporal land use information to plan for future land uses and mitigate adverse impacts. Here, we use spatially-explicit logistic regression analysis and methods from remote sensing and geographic information systems (GIS) to model the relationship between land use factors and forest patches using information from satellite images from the Tano-Offin Forest Reserve in Ghana. The study finds that it is 3,350 times more likely for forest patches that are not within 1 km from barren grounds to be greater than the mean patch size of forest (800 m2) (CI = 297-37,785, P = 0.000). Also, the study finds that it is 2,365 times more likely for the forest patches that are not within 1 km from access roads to be greater than the mean patch size of forest (CI=245-22,776; P = 0.000). These findings suggest that to maintain larger and contiguous patches of forest cover, there is a need for a policy that prevents the creation and expansion of logging-induced barren grounds. Also, the creation of buffers along access roads will be necessary to prevent further anthropogenic influences that are likely to fragment forest cover.

We wish to introduce QWET, a new version of the free and open-source QGIS plugin for the aquatic ecosystem model WET. QWET is as a graphical user interface for the application, evaluation and experimentation of WET. Several new features have been incorporated since its predecessor and, here, we demonstrate elements of the new plugin by applying it to Danish Lake Ravn. Among others, we compare model simulations against observations and describe how the scenario platform now supports scheduling of state-variable manipulation, which allows users to explore lake or reservoir restoration interventions such as biomanipulation and oxygenation. With QWET, we seek to aid practitioners who do not possess the sufficient technical expertise to operate a state-of-the art complex model system, such as WET, and thereby hope to facilitate a wider use and adaptation of aquatic ecosystem models.

Water resources allocation decisions have always been subject to uncertainty, but it has rarely been explicitly included. Greater competition for scarce resources and future uncertainties in supply suggest that risk estimates are required for different management decisions. Models are often used to generate information that can be used in decision making and a water allocation model is presented that is linked to an existing hydrological model that generates uncertainty ensembles and a model that generates environmental water requirements. The allocations are based on socio-economic values that quantify the impact of deficits in normal supply during dry periods when available water is reduced. It is designed to be flexible in terms of how allocations are made during deficit periods and provides outputs that account for the uncertainties in the input hydrological data. Two examples are provided to illustrate the application of the model and it is concluded that the outputs should be useful when combined with emerging approaches to uncertain decision-making and the identification of risk. The model is part of a broader project that aims to improve the way that uncertainty is dealt with in water resources decision-making.

Across the world, stakeholders are asking questions of their governments and decision makers to quantify the risks of environmental threats to their well-being. These questions manifest themselves as ‘deceptively simple questions’, which are easy to articulate but difficult to solve. An example of which is: ‘how much will the eruption of an Icelandic volcano cost the UK economy’. Answering these questions requires predictions of the interaction of multiple environmental processes, this requires the development and maintenance of systems that allow these processes to be simulated, and that is the nascent science of integrated environmental modelling (IEM). Such processes may be long-term (e.g. those that are impacted by climate change) or short-term threats, such as the impact of drought on UK agriculture or the impact of space weather on energy supply systems.

This study aimed to quantify the environmental fate of antimicrobials applied in Fenneropenaeus chinensis aquaculture production in China and to assess their potential risks for surrounding aquatic ecosystems, for the promotion of antimicrobial resistance in target and non-target bacteria and for consumers eating shrimp products that contain antimicrobial residues. For this, we first used the results of an environmental monitoring study performed with the antimicrobial sulfamethazine to parameterize and calibrate the ERA-AQUA model, a mass balance model suited to perform risk assessments of veterinary medicines applied in aquaculture ponds. Next, a scenario representing F. chinensis production in China was built and used to perform risk assessments for 21 antimicrobials which are regulated for aquaculture in China. Results of the model calibration showed a good correspondence between the predicted and the measured sulfamethazine concentrations, with differences within an order of magnitude. Results of the ecological risk assessment showed that four antimicrobials (levofloxacin, sarafloxacin, ampicillin, sulfadiazine) are expected to have adverse effects on primary producers, while no short-term risks were predicted for invertebrates and fish exposed to farm wastewater effluents containing antimicrobial residues. Half of the evaluated antimicrobials showed potential to contribute to antimicrobial resistance in bacteria exposed to pond water and farm effluents. A withdrawal period of three weeks is recommended for antimicrobials applied via oral administration to F. chinensis in order to comply with the current national and international toxicological food safety standards. The results of this study indicate the need to improve the current regulatory framework for the registration of aquaculture antimicrobials in China and suggest compounds that should be targeted in future aquaculture risk assessments and environmental monitoring studies.

We profile the utility and limits in deployment of inexpensive disposable sensor networks by amateurs to achieve environmental monitoring goals. Four current technology movements — PC-on-a-chip processors such as Arduino, prebuilt sensors, 3-D printing, and Wi-Fi and mesh networking — enable rapid sensor platform creation and make it easy for non-specialists to create general sensor-bearing platforms. Deployment of a cluster of multiple sensor-bearing platforms is, however, communications-limited in terms of both range and number of devices supported, and generally requires a base station with internet access. We examine how inexpensive technology supports scenarios for short-term environmental modelling by average citizens.

The pathway of a modelling project is commonly described as an adaptively adjusted chain of steps at which various decisions are made. Communication and documentation about these decisions are crucial to enabling reflection and adapting the pathway to changing circumstances, such that well-informed planning is required. Project decision making, however, often remains a black box; it is rare to find reporting of dead ends, alternative decisions, and changes in decisions during the project. This paper uses an integrated environmental management case study in Iran to demonstrate the importance of reflective documentation and communication within the pathway. We show how a pathway diagram, incorporating some 14 symbols depicting steps, decision forks, options (selected and alternatives), actions, communication and documentation, can illustrate the role of communication within the project and identify lessons learnt. We also encourage further work on application of agile project management and social science techniques to improve modelling practices.

Experimental or numerical analysis of the response of ships and other floating structures starts with correct environmental modelling. The capabilities of numerical tools are rapidly expanding, but presently the evaluation of extreme events in waves (such as slamming, green water, air-gap exceedance) still requires a combination of experiments and different levels of numerical tools. The present paper describes recent efforts within the Maritime Research Institute Netherlands (MARIN) to improve experimental and numerical wave modelling and especially their combination. The ultimate objective is to be able to reproduce any wave condition from a basin or from sea in numerical tools and vice versa, including a sound treatment of basin effects, numerical effects and statistical variability. The aspects that are of importance in both types of wave modelling are first introduced, after which a number of examples of recent projects is discussed. It can be concluded that important steps were made towards linking experimental and numerical wave modelling, but there are some challenges common to all wave reproductions. Some future planned studies focussing on how to deal with them are discussed as well.

We develop and implement a numerical model to simulate the effect of photocatalytic asphalt on reducing the concentration of nitrogen monoxide (NO) due to the presence of heavy traffic in an urban environment. The contributions in this paper are threefold: we model and simulate the spread and breakdown of pollution in an urban environment, we provide a parameter estimation process that can be used to find missing parameters, and finally, we train and compare this simulation with different data sets. We analyse the results and provide an outlook on further research.

The existing HVAC system on board Landing Platform Docks (LPD)s, has been designed to operate in mild tropical environmental conditions such as the Mediterranean. This means that when the ship operates in extreme hot climates such as the Arabian Gulf and the Red sea region, the HVAC system is over loaded and cannot maintain the required design conditions. This results in uncomfortable and difficult working conditions for the ship’s occupants, and causes problems with equipment overheating, and overloading of cooling plants. In order to assess options for improving the HVAC system, an environmental model that is capable of dynamically simulating the environment inside the ship is created. The model takes into account weather data based on ship location and time, ship structure and insulation, sun location and shading effects, internal heat gains from equipment and people, and the performance of the HVAC systems; which includes chillers, cooling coils, heaters, controllers, etc. The environmental model is used to assess options for improving the HVAC system to accommodate extreme tropical conditions. The model also forms an environmental baseline for the ship that can be used for assessing the impact of any change in the operational profile of the ship.

Made available in DSpace on 2019-10-06T15:58:01Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-12-30 Mercury pollution of water bodies exerts significant human and ecosystem health impacts due to high toxicity. Relatively high levels of mercury have been detected in the Amazon River and its tributaries and associated lakes. The study employed a Bayesian Network approach to investigate the contribution from geogenic sources to mercury pollution of lakes in the Madeira River basin, which is the largest tributary of the Amazon River. It was found that the source indicators of naturally occurring mercury have both, positive and negative relationships with mercury in lake sediments. Although the positive relationships indicated the influence of geological and soil formations, the negative relationships implied that the use of mercury amalgam for gold extraction in artisanal and small-scale mining (ASM), which is the primary anthropogenic source of mercury, also contribute to mercury in Amazon tributaries. This was further evident as mercury concentrations in lake sediments were found to be significantly higher than those in the surrounding rocks. However, potential anthropogenic mercury was attributed to historical inputs from gold mining due to the recent decline of ASM mining practice in the region. Departamento de Petrologia e Metalogenia Universidade Estadual Paulista (UNESP) Câmpus de Rio Claro, Av. 24-ANo.1515, C.P. 178 College of Chemistry and Environmental Engineering Shenzhen University Science and Engineering Faculty Queensland University of Technology (QUT), GPO Box 2434 Fundação Universidade Federal de Rondônia (UNIR), Av. Presidente Dutra No. 2965 Departamento de Petrologia e Metalogenia Universidade Estadual Paulista (UNESP) Câmpus de Rio Claro, Av. 24-ANo.1515, C.P. 178

Information on global future gridded emissions and land-use scenarios is critical for many climate and global environmental modelling studies. Here, we generated such data using an integrated assessment model (IAM) and have made the data publicly available. Although the Coupled Model Inter-comparison Project Phase 6 (CMIP6) offers similar data, our dataset has two advantages. First, the data cover a full range and combinations of socioeconomic and climate mitigation levels, which are considered as a range of plausible futures in the climate research community. Second, we provide this dataset based on a single integrated assessment modelling framework that enables a focus on purely socioeconomic factors or climate mitigation levels, which is unavailable in CMIP6 data, since it incorporates the outcomes of each IAM scenario. We compared our data with existing gridded data to identify the characteristics of the dataset and found both agreements and disagreements. This dataset can contribute to global environmental modelling efforts, in particular for researchers who want to investigate socioeconomic and climate factors independently. Machine-accessible metadata file describing the reported data (ISA-Tab format)

Environmental modelling combined with scenarios provides insights into drivers of change, potential implications of different trajectories, and options for action. So far, there has been no endeavor to assess the breadth of assumptions concerning drivers of ecosystem change on a global and European level as used in various scenario approaches. Our paper fills this gap by reviewing drivers of 27 global and European scenarios to provide an overview of extreme assumptions. Additionally, results can support quantification efforts of storylines to test environmental and ES models and to facilitate participatory scenario development to improve the usefulness of modelling approaches for stakeholders.

The assessment of the environmental impact of tritium release from nuclear facilities is a topic of interest in many countries. In the IAEA's Environmental Modelling for Radiation Safety (EMRAS I) programme, progresses for routine releases were done and in the EMRAS II programme a dedicated working group (WG 7 - Tritium Accidents) focused on the potential accidental releases (liquid and atmospheric pathways). The progresses achieved in WG 7 were included in a complex report - a technical document of IAEA covering both liquid and atmospheric accidental release consequences. A brief description of the progresses achieved in the frame of EMRAS II WG 7 is presented. Important results have been obtained concerning washout rate, the deposition on the soil of HTO and HT, the HTO uptake by leaves and the subsequent conversion to OBT (organically bound tritium) during daylight. Further needs of the processes understanding and the experimental efforts are emphasised.

There is an increasing need for environmental management advice that is wide-scoped, covering various interlinked policies, and realistic about the uncertainties related to the possible management actions. To achieve this, efficient decision support integrates the results of pre-existing models. Many environmental models are deterministic, but the uncertainty of their outcomes needs to be estimated when they are utilized for decision support. We review various methods that have been or could be applied to evaluate the uncertainty related to deterministic models' outputs. We cover expert judgement, model emulation, sensitivity analysis, temporal and spatial variability in the model outputs, the use of multiple models, and statistical approaches, and evaluate when these methods are appropriate and what must be taken into account when utilizing them. The best way to evaluate the uncertainty depends on the definitions of the source models and the amount and quality of information available to the modeller. We review different types of uncertainty present in environmental modelling.We review methods to evaluate uncertainty related to model results.Best way to evaluate uncertainty depends on the models and available information.

Integrated environmental modelling (IEM) couples interdependent environmental models and data together to solve complex environmental problems. There are two major modelling frameworks for IEM: component based framework, and service oriented framework. This paper suggests to take the best of both to couple modelling components and services together. The result is a hybrid method to leverage Open Modelling Interface (OpenMI) and WebSocket for coupling components and services together to provide a more flexible IEM environment.

The discipline of Integrated Environmental Modelling (IEM) has developed in order to solve complex environmental problems, for example understanding the impacts of climate change on the physical environment. IEM provides methods to fuse or link models together, this in turn requires facilities to make models discoverable and also to make the outputs of modelling easily visualized. The vision and challenges for IEM going forward are summarized by leading proponents. Several case studies describe the application of model fusion to a range of real-world problems including integrating groundwater and recharge models within the UK Environment Agency, and the development of ‘catastrophe’ models to predict better the impact of natural hazards. Communicating modelling results to end users who are often not specialist modellers is also an emerging area of research addressed within the volume. Also included are papers that highlight current developments of the technology platforms underpinning model fusion.

We present a powerful method to extract per-point semantic class labels from aerialphotogrammetry data. Labeling this kind of data is important for tasks such as environmental modelling, object classification and scene understanding. Unlike previous point cloud classification methods that rely exclusively on geometric features, we show that incorporating color information yields a significant increase in accuracy in detecting semantic classes. We test our classification method on three real-world photogrammetry datasets that were generated with Pix4Dmapper Pro, and with varying point densities. We show that off-the-shelf machine learning techniques coupled with our new features allow us to train highly accurate classifiers that generalize well to unseen data, processing point clouds containing 10 million points in less than 3 minutes on a desktop computer., Comment: ISPRS 2017

Background Tick populations and tick-borne infections have steadily increased since the mid-1990s posing an ever-increasing risk to public health. Yet, modelling tick dynamics remains challenging because of the lack of data and knowledge on this complex phenomenon. Here we present an approach to model and map tick dynamics using volunteered data. This approach is illustrated with 9 years of data collected by a group of trained volunteers who sampled active questing ticks (AQT) on a monthly basis and for 15 locations in the Netherlands. We aimed at finding the main environmental drivers of AQT at multiple time-scales, and to devise daily AQT maps at the national level for 2014. Method Tick dynamics is a complex ecological problem driven by biotic (e.g. pathogens, wildlife, humans) and abiotic (e.g. weather, landscape) factors. We enriched the volunteered AQT collection with six types of weather variables (aggregated at 11 temporal scales), three types of satellite-derived vegetation indices, land cover, and mast years. Then, we applied a feature engineering process to derive a set of 101 features to characterize the conditions that yielded a particular count of AQT on a date and location. To devise models predicting the AQT, we use a time-aware Random Forest regression method, which is suitable to find non-linear relationships in complex ecological problems, and provides an estimation of the most important features to predict the AQT. Results We trained a model capable of fitting AQT with reduced statistical metrics. The multi-temporal study on the feature importance indicates that variables linked to water levels in the atmosphere (i.e. evapotranspiration, relative humidity) consistently showed a higher explanatory power than previous works using temperature. As a product of this study, we are able of mapping daily tick dynamics at the national level. Conclusions This study paves the way towards the design of new applications in the fields of environmental research, nature management, and public health. It also illustrates how Citizen Science initiatives produce geospatial data collections that can support scientific analysis, thus enabling the monitoring of complex environmental phenomena.

This paper builds on reverse combinatorial auctions theory and its selected environmental applications, which were presented at ISESS 2013 and ISESS 2015. It provides an approach for calculating the sensitivity and proposals for necessary adjustments of CombinatoRial Auction Body Software System (CRAB), which makes its use for the relevant decision-making tasks more user friendly. Two possibilities are suggested. The first approach is appropriate for cases with relatively small numbers of subjects, where it is possible to compute all feasible solutions ordered by total cost. In such cases it is possible to analyse changes of coalition structures with increasing the cost. The second one suggests modification of the CRAB software, which would make it possible to analyse cases with high numbers of feasible coalition structures located between the optimal coalition (i.e. the cost-effective one) and the structure consisting of individual projects. This approach is appropriate for complex real applications involving setting of cost levels.

An important challenge facing the New Zealand (NZ) dairy industry is development of production systems that can maintain or increase production and profitability, while reducing impacts on receiving environments including water and air. Using research &lsquo, farmlets&rsquo, in Waikato, Canterbury, and Otago (32&ndash, 200 animals per herd), we assessed if system changes aimed at reducing nitrate leaching can also reduce total greenhouse gas (GHG) emissions (methane and nitrous oxide) and emissions intensity (kg GHG per unit of product) by comparing current and potential &lsquo, improved&rsquo, dairy systems. Annual average GHG emissions for each system were estimated for three or four years using calculations based on the New Zealand Agricultural Inventory Methodology, but included key farmlet-specific emission factors determined from regional experiments. Total annual GHG footprints ranged between 10,800 kg and 20,600 kg CO2e/ha, with emissions strongly related to the amount of feed eaten. Methane (CH4) represented 75% to 84% of the total GHG footprint across all modelled systems, with enteric CH4 from lactating cows grazing pasture being the major source. Excreta deposition onto paddocks was the largest source of nitrous oxide (N2O) emissions, representing 7&ndash, 12% of the total GHG footprint for all systems. When total emissions were represented on an intensity basis, &lsquo, systems are predicted to generally result in lower emissions intensity. The &lsquo, systems had lower GHG footprints than the &lsquo, current&rsquo, system, except for one of the &lsquo, systems in Canterbury, which had a higher stocking rate. The lower feed supplies and associated lower stocking rates of the &lsquo, systems were the key drivers of lower total GHG emissions in all three regions. &lsquo, Improved&rsquo, systems designed to reduced N leaching generally also reduced GHG emissions.

The KUBUS conference centre at the Helmholtz Centre for Environmental Research in Leipzig, Germany, hosted the Sixth Biennial Congress on Environmental Modelling and Software from July 1st to 5th, 2012. The meeting welcomed more than 430 scientists from 33 countries under the overarching theme "Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty". Here, we report on the outcomes of the congress, but most of all, we provide insights from behind the scenes, showing how the meeting was developed along four key objectives: (i) to provide an excellent environment for scientific exchange, (ii) to support young academics and early career scientists, (iii) to perform outreach activities to promote the event (and environmental modelling) among broader public and (iv) to act as an environmentally friendly meeting. Thus, this commentary suggests a blueprint and provides templates and ideas for upcoming similar conferences.

Recycling is an important part of waste management (that includes different kinds of issues: environ- mental, technological, economic, legislative, social, etc.). Differently from many works in literature, this paper is focused on recycling management and on the dynamic optimization of materials collection. The developed dynamic decision model is characterized by state variables, corresponding to the quantity of waste in each bin per each day, and control variables determining the quantity of material that is col- lected in the area each day and the routes for collecting vehicles. The objective function minimizes the sum of costs minus benefits. The developed decision model is integrated in a GIS-based Decision Support System (DSS). A case study related to the Cogoleto municipality is presented to show the effectiveness of the proposed model. From optimal results, it has been found that the net benefits of the optimized col- lection are about 2.5 times greater than the estimated current policy.

There has been a rapidly growing interest among contemporary architects in recent years in the innovative use of curtain walls as a building enclosure. A curtain wall is a glass and metal skin that wraps the entire building in a continuous, transparent layer. This modern design provides a relatively desirable environment for the occupants. The glass façade allows light and diffused views into the surroundings during the day and can become a glowing and aesthetically pleasing aspect of the skyline at night. The key visual features of curtain walls are the glazing appearance and sightlines, but the window selection plays a key role in determining the overall building's environmental performance. The complex layering of glass should be strategic as well as artistic, balancing light and shade to optimize light and minimize heat gain. Recently, a series of curtain wall system have been developed with an emphasis on the technical issues, such as structural stability, energy efficiency, sustainable strategies, daylighting, and materials. This design case project explores in depth the overall environmental performance of the leading-edge curtain wall assemblies using computer programs such as Virtual Environment and Radiance, which allow estimation of total U-values and helps predict daylighting performance.

Time-series are an important aspect of environmental modelling, and are becoming more available through the requirements of the water framework directive as well as more important with the advancement of numerical simulation techniques and increased model complexity. For this reason, within the H2020 FREEWAT project, which aims at facilitating the adoption of modeling for water resource management, the integration of a tool for time-series analysis and processing has been foreseen. As a result the Observation Analysis Tool was developed to enable time-series visualisation, pre-processing of data for model development, and post-processing of model results. Observation Analysis Tool can act as a pre-processor for calibration observations, and will be expanded to incorporate its processing capabilities directly into the calibration process. The tool consists in an expandable Python library and in an interface integrated in the QGIS FREEWAT plug-in which include a large number of modelling capabilities, hydro-chemical data management tools and calibration capacity. The tool has been extensively used and tested in different european institutions, to collect a number of indications to drive the future development.

The discipline of ecological modeling has been developed since the 1970s, a process that has been evolving quickly due to development of proper techniques, computer power, and adequate software, together with the recognition of existence of environmental problems, as well as the establishment of sufficient knowledge on ecological processes, how they are regulated, and hence how to retain ecosystem properties. At the beginning, our understanding was based on rudimentary solutions like introduction of various environmental technologies but later management was expanded by extensive use of models assisted by use of more advanced technologies, regulatory and legislative initiatives. This was necessary as the environmental problems we had to address soon turned out to exhibit an almost ever-increasing complexity. Ecological models can be used for survey, to reveal system properties, establish research priorities, and to test scientific hypotheses. Hence, we consider them useful as experimental tools. A basic grouping shows that ecological models in general belong to three areas: biodemographic, bioenergetic, and biogeochemical. Technically, the models have been developed within a set of 14 different approaches which results in almost 300 papers published per year about ecological modeling in the journal of Ecological Modelling alone. This represents a 16-fold increase in pages published as compared to the late 1970s. In the recent decades, ecological modeling has also developed in a direction to include theoretical studies of ecosystems, such as the possibility of goal oriented behavior, understanding of complexity, and organizational issues.

We propose the TEMPORANA framework for analysis of integrated scenarios aiming at studying the possible effects on the society of sustainable innovation policies. The framework consists of a set of advanced temporal queries for scenario analysis and a software application. Integrated scenarios are possible future states of different aspects of the world (e.g., energy, environment, technology, economy, societal system) representing plausible conditions under different assumptions. Temporal scenario queries aim at detecting a specified behavior for the system over time and, hence, at verifying that a temporal property holds.

Every year, the Editors of Environmental Modelling and Software select ten outstanding reviewers who have provided exceptional contributions to the journal. These ‘Outstanding Reviewer Award’ recipients are shortlisted by the Editors based on the rigor, constructiveness and timeliness of their reviews in addition to the number of reviews performed.