Environmental Data Exchange Research Articles

The interactive indoor-outdoor building energy modeling for enhancing the predictions of urban microclimates and building energy demands

There is a lack of an urban building energy modeling framework that considers the influence of surrounding buildings and local urban climate on building thermal performance. This can lead to inaccurate results since the thermal performance of individual buildings is heavily influenced by their surrounding built and climatic environment. This study establishes an interactive indoor-outdoor building energy modeling method to enhance the predictions of urban microclimates and building energy demands by coupling an urban physics model with a physics-based building energy model. Validation of the interactive coupling scheme uses field measurement datasets. Parametric simulation and analysis are conducted to understand the influence of the roof-to-canyon width ratio, canyon orientation, and ground vegetation fraction on canyon temperature, building energy consumption, and energy demand. Furthermore, the impacts of building energy model complexity (e.g., detailed vs. simplified building models) and coupling approaches on canyon temperature and building energy profiles are demonstrated using two case study buildings. In comparison with the one-way coupling approach, cooling energy consumption predicted with the dynamic two-way coupling approach varies by 3.5 % and 0.5 % for the detailed medium office building model and high-rise building model, respectively, and peak cooling demand varies by 8.4 % and 7.0 % for the detailed medium office building model and high-rise building model, respectively. This study also suggests that adopting a complex two-way coupling approach with environmental data exchange at various elevations is necessary for modeling tall buildings at the urban scale.

Improving the regulatory environmental risk assessment of human pharmaceuticals: Required changes in the new legislation

One of the flagship actions of the Pharmaceutical Strategy for Europe is to address environmental challenges associated with pharmaceutical use. This includes strengthening the Environmental Risk Assessment (ERA) at marketing authorisation (MA) of pharmaceuticals, and revision of the pharmaceutical legislation where needed. The overall aim of an ERA should be to enable comprehensive and effective identification and management of environmental risks of pharmaceuticals without affecting the availability of pharmaceuticals to patients. As experts in the evaluation of ERAs of human medicinal products submitted by pharmaceutical industries (Applicants), we have summarized the current status of the ERA and suggest legislative changes to improve environmental protection without affecting availability. Six regulatory goals were defined and discussed, including possible ways forward: 1) mandatory ERAs in accordance to the EMA guideline at the time of the MA, 2) enforcement of risk mitigation measures including re-evaluation of the ERA, 3) facilitated exchange of environmental data between pharmaceutical and environmental legislations, 4) substance-based assessments, 5) transparency of data, and 6) a catching-up procedure for active pharmaceutical ingredients that lack an ERA. These legislative proposals can be considered as prerequisites for a harmonised assessment and effective management of environmental risks and hazards of human pharmaceuticals.

A Proof-of-Concept IoT System for Remote Healthcare Based on Interoperability Standards.

The Internet of Things paradigm in healthcare has boosted the design of new solutions for the promotion of healthy lifestyles and the remote care. Thanks to the effort of academia and industry, there is a wide variety of platforms, systems and commercial products enabling the real-time information exchange of environmental data and people’s health status. However, one of the problems of these type of prototypes and solutions is the lack of interoperability and the compromised scalability in large scenarios, which limits its potential to be deployed in real cases of application. In this paper, we propose a health monitoring system based on the integration of rapid prototyping hardware and interoperable software to build system capable of transmitting biomedical data to healthcare professionals. The proposed system involves Internet of Things technologies and interoperablility standards for health information exchange such as the Fast Healthcare Interoperability Resources and a reference framework architecture for Ambient Assisted Living UniversAAL.

ОРГАНИЗАЦИЯ ПРОИЗВОДСТВЕННОГО МОНИТОРИНГА ЖИЗНЕННОГО ЦИКЛА ПРОИЗВОДСТВА СОПОЛИМЕРА С ИСПОЛЬЗОВАНИЕМ ТЕХНОЛОГИЙ LCA

The article is devoted to the actual problem of organizing industrial environmental monitoring of the life cycle of production using information technology. In order to provide Russian enterprises with methodological recommendations for organizing a system of production control and monitoring in order to comply with legislation on maximum environmental standards and waste turnover, it is necessary to study and develop possible options for accumulating data and converting them automatically. The purpose of the article is to develop solutions for organizing a system for monitoring the impact of the stages of the life cycle of petrochemical production on the external environment using tools for continuous information support. To design information modules for assessing the impact of production processes on the ecosystem, sequential procedures of the LCA method were used. To optimize the parameters of environmental friendliness of the production of styrene-butadiene copolymer, the article solves the problem of linear programming; the database for solving the linear programming problem is based on materials from information and technical reference books on the best available technologies, reference books on standards for maximum permissible concentrations of pollutants. The use of the method of information support of the life cycle of LCA products for the organization of automated industrial environmental control and monitoring is scientifically substantiated. A model of the production chain is formed and a block diagram is presented for assessing the impact of the life cycle of chemical production on the ecosystem using the LCA method in the absence of a standardized technology for the accumulation and exchange of environmental data, various levels of automation and digitalization of production processes in petrochemical industries. The flows at the boundary of the chemical-technological system for the production of styrene-butadiene copolymer are investigated and a possible variant of their mathematical optimization is proposed. By solving the linear programming problem, the optimal values of resource consumption for the production of butadiene-styrene copolymer were obtained, at which the minimum indicators of pollutant emissions into the ecosystem are possible: butadiene - 725 kg/t; styrene – 313 kg/t; electricity – 830 kWh/t; water steam - 9.0 Gcal / t. Examples of chemical-technological systems have been identified, where the use of butadiene and styrene relative to the obtained optimal parameter leads to overexpenditure of resources. The research materials can be used in the development of programs and the choice of tools for automated industrial environmental control and monitoring in chemical-technological systems.

Supervised Machine Learning and Heuristic Algorithms for Outlier Detection in Irregular Spatiotemporal Datasets

A central problem in time series analysis is the detection of outliers, with further complications presented by irregular time series data measured having spatiotemporal components. This paper presents one Heuristic and two Supervised Machine Learning algorithms for the detection of outliers in this context in univariate time series data, with comparison of results to Chen and Liu's (1993) automatic outlier detection methodology. Due to the recent trend of set up of large environmental databases across many states in the US and around the world, which allow submission of pollutant measurement data from virtually any source, these procedures are applied to the measurements of various surface water pollutants in the California Environmental Data Exchange Network (CEDEN) for understanding and exploring the viability of such databases and the proposed methods. The proposed methodologies though not as robust, give similar results to existing methodologies given the nature of the data, but can be far less time intensive to implement providing interesting insights into the database. Thus, the algorithms presented can be widely used with minimal computing resource requirements with very tractable results even with very large datasets. The methodologies have wide applicability in a variety of contexts and a wide variety of databases with similar measurement challenges across many disciplines, specifically in the environmental setting. In particular, the results have large potential regulatory impact on accepted levels of different pollutants in California water bodies, as well as the amounts to be charged for industrial discharge into those water bodies, and is intended to provide direction for further research and regulatory investments. Based on the results it seems reasonable to assume that there is further room for the inclusion of nongovernmental agency pollutant measurements in the debate of environmental pollution, specifically in California. However, the results also indicate that the use of such databases in a more inclusive way for regulatory matters must be carefully evaluated on an individualized basis. That is to ensure that poorly collected/handled measurements, do not inundate the database over and above those collected with more rigor, thus potentially making inference on the true population distribution of the pollutants more difficult; being especially relevant for those pollutant measurements, which require more delicate sampling procedures.

Regional impacts of urbanization on stream channel geometry: A case study in semiarid southern California

Urbanization often increases storm runoff, peak discharges and rates of stream channel erosion. Coastal California has experienced rapid urbanization over the past several decades and has the potential for stream channel degradation. Several counties in California have implemented Hydromodification Management Plans (HMPs) to protect channels from erosion, but few studies have quantified the impact of urbanization on channel geometry in diverse geological settings at the county scale. A synoptic survey of field sites (N=56) by the California Environmental Data Exchange Network (CEDEN) and additional field surveys (N=24) were used to develop regional hydraulic geometry curves relating bankfull cross-sectional area (Axs), width (w), mean depth (d), and discharge (Qbf) to watershed area (Aw) in San Diego County. Regional curves were compared for urban and reference sites and to other regional curves developed for southern California. Multiple regression models were used to identify dominant watershed and channel controls on geometry, including Aw, percent impervious cover (I%), mean annual precipitation, underlying geology, longitudinal slope, hydrologic soil group, and channel particle size. For the reference streams, regional curves were statistically significant for w and Axs (p<0.05). The regional curves for urban channels (I%>20%) had significantly larger w, d, Axs, and Qbf for a given watershed size. A majority (68%) of the urban channels and 78% of the small urban channels (Aw<10km2) were enlarged. Enlargement of channels in small watersheds disrupted the correlation between Aw and bankfull dimensions, and I% was the only significant predictor of channel geometry in urban watersheds. Channel response differed by channel substrate: sand-bedded channels incised and experienced extreme enlargement of up to 115× the Axs of reference sites, while gravel-bedded channels widened and showed less enlargement (<7× reference Axs). Diverse channel responses to urbanization were observed at the county scales with significant scatter about the regional curves and regression equations. Urban channels have a high probability of enlargement, with greater risk for sand-bedded streams, but the magnitude of enlargement was not predictable from watershed or channel characteristics.

A Lightweight Approach for the Sensor Observation Service to Share Environmental Data across Europe

AbstractThe importance of near real‐time access to environmental data has increased steadily over the last few years. In this article, the focus is on the European Environment Agency (EEA), which receives environmental data from a large number of providers. The heterogeneous data formats and data transfer mechanisms make the data collection and integration a difficult task for the EEA. An approach is needed for facilitating the interoperable exchange of environmental data on a large scale. A core element of this approach is the Sensor WebEnablement (SWE) technology of the Open Geospatial Consortium (OGC) which allows the standardized, interoperable, vendor and domain independent exchange of sensor data. The main contribution of this article is a lightweight profile for the OGC Sensor Observation Service that ensures the necessary interoperability for seamlessly integrating the environmental data provided by the EEA's member states and thus forms the foundation for the developed data exchange mechanisms. This is complemented by information about the resulting Sensor Web architecture and the integration into the EEA's existing IT infrastructure. In summary, this article describes a practical scenario in which SWE technology enables the exchange of near real‐time environmental data on a large scale.

A Framework for Cooperative Control Applied to a Distributed Sensor Network

This paper proposes and evaluates a framework for cooperative control of a multi-agent system. The framework is evaluated on a target-tracking application where a distributed sensor network is tasked to autonomously observe targets within the environment. The problem of cooperative control is defined using two distinct levels of cooperation: implicit and explicit. Implicit cooperation is defined as cooperation through only the exchange of environmental data to compile a common picture over which to reason locally. For example, in this paper, decentralized data fusion algorithms are used to build and update a common picture of the target positions and velocities. Explicit cooperation, which is the main focus of this paper, negotiates the agents explicitly on a joint set of actions to perform. In this paper, the problem of explicit cooperation is formulated as a distributed optimization, and a framework to find the joint set of actions is proposed. The framework utilizes two algorithms, the Max-Sum algorithm, to globally solve a factorizable utility function, and Probability Collectives (PC), to solve the individual factors of the utility function. The paper presents experimental results of the two algorithms using a simulated distributed sensor network when the tracking problem is and is not factorizable. The results show that the proposed framework can efficiently and effectively enable cooperation in a distributed sensor network. The Max-Sum algorithm provides a distributed and flexible approach to solve a factorizable utility function, where the PC algorithm was shown to efficiently solve the individual factors when more than four sensors are required to cooperate.

Vision of a Cyberinfrastructure for Nonnative, Invasive Species Management

ABSTRACT Although the quantity of data on the location, status, and management of invasive species is ever increasing, invasive species data sets are often difficult to obtain and integrate. A cyberinfrastructure for such information could make these data available for Internet users. The data can be used to create regional watch lists, to send e-mail alerts when a new species enters a region, to construct models of species' current and future distributions, and to inform management. Although the exchange of environmental data over the Internet in the form of raster data is maturing, and the exchange of species occurrence data is developing quickly, there is room for improvement. In this article, we present a vision for a comprehensive invasive species cyberinfrastructure that is capable of accessing data effectively, creating models of invasive species spread, and distributing this information.

ACTIVE INFORMATION GATHERING IN INFOSLEUTHTM

InfoSleuth is an agent-based system that can be configured to perform many different information management activities in a distributed environment. InfoSleuthTM agents provide a number of complex query services that require resolving ontology-based queries over dynamically changing, distributed, heterogeneous resources. These include distributed query processing, location-independent single-resource updates, event and information monitoring, statistical or inferential data analysis, and trend discovery in complex event streams. It has been used in numerous applications, including the Environmental Data Exchange Network and the Competitive Intelligence System.