Environmental Measurement Data Research Articles

Research on the development of AloT sensing module for new energy power information collection

Abstract In order to improve the ability of power communication technology to support large-scale and massive services of smart electricity consumption, this paper designs a sensing model to collect information on new energy electricity consumption. Using the arrival rate calculation method of intelligent IoT, the information on new energy electricity users is collected, and the environmental measurement data is collected with the help of intelligent sensors. Monitoring the concurrency factor of all sensors in the operation state, collecting queuing theory packet loss rate through utilization maximization objective function, and setting the average queuing length of communication nodes. On this basis, the voltage amplitude of the electrical energy sampling point is measured, and the Gaussian perceptual loss vector with non-zero mean and heteroskedasticity is performed to iteratively converge the constraint matrix and error covariance. The results show that the maximum relative errors for service delay and packet loss rate are 16.8% and 7.0%, respectively. As bandwidth increases, the queuing delay and packet loss rate decrease. The broadband power line carrier can reach up to 210 Mbps, and the micropower wireless rate can reach 38.5 kbps. The annual cycle characteristics fluctuate widely, but the cumulative error of electricity load prediction results is lower, and the prediction accuracy is high. It shows that the electricity consumption information collection sensing model provides an important reference for building a new communication network with low cost, high speed and reliability for smart electricity consumption.

Updated Prediction of Air Quality Based on Kalman-Attention-LSTM Network

The WRF-CMAQ (Weather research and forecast-community multiscale air quality) simulation system is commonly used as the first prediction model of air pollutant concentration, but its prediction accuracy is not ideal. Considering the complexity of air quality prediction and the high-performance advantages of deep learning methods, this paper proposes a second prediction method of air pollutant concentration based on the Kalman-attention-LSTM (Kalman filter, attention and long short-term memory) model. Firstly, an exploratory analysis is made between the actual environmental measurement data from the monitoring site and the first forecast data from the WRF-CMAQ model. An air quality index (AQI) was used as a measure of air pollution degree. Then, the Kalman filter (KF) is used to fuse the actual environmental measurement data from the monitoring site and the first forecast results from the WRF-CMAQ model. Finally, the long short-term memory (LSTM) model with the attention mechanism is used as a single factor prediction model for an AQI prediction. In the prediction of O3 which is the main pollutant affecting the AQI, the results show that the second prediction based on the Kalman-attention-LSTM model features a better fitting effect, compared with the six models. In the first prediction (from the WRF-CMAQ model), for the RNN, GRU, LSTM, attention-LSTM and Kalman-LSTM, SE improved by 83.26%, 51.64%, 43.58%, 45%, 26% and 29%, respectively, RMSE improved by 83.16%, 51.52%, 43.21%, 44.59%, 26.07% and 28.32%, respectively, MAE improved by 80.49%, 56.96%, 46.75%, 49.97%, 26.04% and 27.36%, respectively, and R-Square improved by 85.3%, 16.4%, 10.3%, 11.5%, 2.7% and 3.3%, respectively. However, the prediction results for the Kalman-attention-LSTM model proposed in this paper for other five different pollutants (SO2, NO2, PM10, PM2.5 and CO) all have smaller SE, RMSE and MAE, and better R-square. The accuracy improvement is significant and has good application prospects.

ESTIMATION OF PROTECTION FACTORS FOR SURROGATE VEHICLE MODELS IN ENVIRONMENTAL CONTAMINATION SCENARIOS.

In the event of a nuclear or radiological incident involving the release of radioactive material, it may be critical to estimate doses to individuals who are transported through contaminated areas by vehicles. The radiation protection factor (RPF) for vehicles can be calculated to determine the level of shielding protection by the vehicle from external radiation sources. Prior studies evaluating RPFs demonstrate a lack of realistic vehicle configurations and the results cannot be extended directly to scenarios where a vehicle is surrounded by a contaminated environmental field. In this work, sex-averaged effective dose-rate coefficients were computed employing International Commission on Radiological Protection Publication 103 recommendations for radionuclides of interest and used to calculate the RPF as the ratio of unshielded to shielded dose for various radionuclides of interest in consequence management scenarios. Comparisons to dose reduction factors calculated using environmental measurement data from the 2011 Fukushima Daiichi nuclear incident were conducted to benchmark to experimental field measurements.

Ecotoxicological risk ranking of 19 metals in the lower Yangtze River of China based on their threats to aquatic wildlife

With thousands of chemicals discharged into the aquatic environment, it is necessary to identify those that are likely to be having the greatest impact on wildlife to better protect the ecosystem. A risk ranking approach was developed to compare the ecotoxicological risk of chemicals on aquatic wildlife with a wide range of environmental measurement data and ecotoxicity data. Nineteen metals including some rarely monitored ones including antimony (Sb), molybdenum (Mo), cobalt (Co), vanadium (V), titanium (Ti) and thallium (Tl) in the lower Yangtze River were risk ranked as a case study. The risk ranking approach was conducted in three tiers: general risk ranking, lethal effects vs. non-lethal effects risk ranking, and species group-specific risk ranking. Iron, copper and titanium were identified as being of greatest concern. The contamination of iron, zinc, copper and nickel was widespread and may have already harmed wildlife according to the overlap between ecotoxicity and monitored levels. Based on this analysis, the risk from copper and some rarely monitored metals (titanium and boron) may have been underestimated. Greater efforts to reduce copper, iron and titanium contamination could make an important difference to the health of Chinese freshwater organisms in the Yangtze River.

Analysis of Environmental Data to Support Quantification of Historical Releases from a Former Uranium Processing Facility in Apollo, Pennsylvania.

This paper describes how environmental measurement data were used to help quantify the spatial impact and behavior of uranium released to the environment from a uranium manufacturing facility in Apollo, PA. The Apollo facility released enriched uranium to the environment while it operated between 1957 and 1983. Historical monitoring data generated by the site, along with other independent data sources, provided a long-term record documenting the presence and behavior of uranium in the local environment. This record of evidence, together with reconstructed estimates of facility releases, has been used to estimate environmental concentrations during facility operations and potential exposures to members of the public. Historical environmental measurement data were also used to confirm predictions of deposition and concentrations in air. The data are used here to derive atmospheric deposition velocities for the uranium emissions. Based on the spatial pattern of measurements and calculated deposition velocities around the facility, the released material contained larger particles that deposited close to the facility, and the released material remains largely in the surface layers of the soil, indicating limited downward mobility. Evidence of measurable impacts was determined to extend a relatively short distance (<500 m) from the facility. The soil data collected around Apollo are also compared to findings related to uranium mobility at another facility where uranium was released to the environment, and similar behavior was observed at both sites.

Estimating Lung Deposition of Fungal Spores Using Actual Airborne Spore Concentrations and Physiological Data.

Exposure to bioaerosols has been implicated in adverse respiratory symptoms, infectious diseases, and bioterrorism. Although these particles have been measured within residential and occupational settings in multiple studies, the deposition of bioaerosol particles within the human respiratory system has been only minimally explored. This paper uses real-world environmental measurement data of total fungal spores using Air-o-Cell cassettes in 16 different apartments and residents' physiological data in those apartments to predict respiratory deposition of the spores. The airborne spore concentrations were measured during the spring, summer, and fall. The respiratory deposition of five most prevalent spore genera-Ascospores, Aspergillus, Basidiospores, Cladosporium, and Myxomycetes-was predicted using three empirical models: the Multiple Path Particle Dosimetry model, using both the Yeh and age-specific versions, and the Bioaerosol Adaptation of the International Committee on Radiological Protection's Lung deposition model. The predicted total deposited number of spores was highest for Ascospores and Cladosporium. While the majority of spores deposit were in the extrathoracic region, there is a significant deposition for both Aspergillus and Cladosporium in the alveolar region, potentially leading to the development of aspergillosis or allergic asthma. Although the dose-response relationship is unknown, the estimate of the actual spore deposition could be the first step in determining such a relationship.

Use of Routine Environmental Monitoring Data to Establish a Dose-based Compliance System for a Low-level Radioactive Waste Disposal Site.

A dose-based compliance methodology was developed for Waste Control Specialists, LLC, low-level radioactive waste facility in Andrews, Texas, that allows routine environmental measurement data to be evaluated not only at the end of a year to determine regulatory compliance, but also throughout the year as new data become available, providing a continuous assessment of the facility. The first step in the methodology is a screening step to determine the potential presence of site emissions in the environment, and screening levels are established for each environmental media sampled. The screening accounts for spatial variations observed in background for soil and temporal fluctuations observed in background for air. For groundwater, the natural activity concentrations in groundwater wells at the facility are highly variable, and therefore the methodology uses ratios for screening levels. The methodology compares the ratio of gross alpha to U + U to identify potentially abnormal alpha activity and the ratio of U to U to identify the potential presence of depleted uranium. Compliance evaluation is conducted for any samples that fail the screening step. Compliance evaluation uses the radionuclide-specific measurements to first determine (1) if the dose exceeds the background dose and if so, (2) the dose consequences, so that the appropriate investigation or action occurs. The compliance evaluation is applied to all environmental samples throughout the year and on an annual basis to determine regulatory compliance. The methodology is implemented in a cloud-based software application that is also made accessible to the regulator. The benefits of the methodology over the existing system are presented.

METEO: Estación de monitorización meteorológica remota

&#x0D; Este artículo se centra en el diseño y desarrollo de una Estación de Monitorización Meteorológica Remota, fundamentada en la imposición de una serie de requisitos, como es la monitorización de magnitudes medioambientales (Temperatura, Humedad, Presión Atmosférica, Calidad del Aire, Iluminación Ambiental, Lluvia y Ruido), la medición, el almacenamiento y la creación de históricos de las magnitudes anteriores; siguiendo para ello la metodología del modelo de ciclo de vida en ‘V’. El proyecto se basa en el uso de elementos de bajo coste (que puedan estar disponibles para el público en general) y en técnicas que minimicen el consumo de los elementos y sistemas electrónicos (configuración de sensores para conmutar a estados de apagado o reposo y codificación de las aplicaciones software para entrada en espera de los procesos en ejecución). En base a los requisitos del proyecto, se planificaron una serie de pruebas para la validación y verificación del producto, en cada una de sus fases; evidenciando que el seguimiento de una metodología de trabajo (que define cada etapa del proyecto), redunda en una implementación satisfactoria del proyecto.

Sheltering of stone art

Application of shelters during the winter season has a tradition for high grade stone decorations of some parks, castles and cathedrals in Central Europe. The often delicate sculptures from world famous artists exposed outdoors in parks and gardens are covered seasonally by mobile shelter systems. Quite different systems of protective sheltering for winter covers are to be distinguished. These encompass wrapping techniques and several types of boxes used to cover sculptures for protection. Recently, systems made out of new materials have come to the market and extend the stock. The distribution of those different winter cover types in Europe seems to reflect local traditions. Here, the different seasonal shelter types are presented, differentiated and evaluated, and important recommendations given for decision making on the application of protective winter covers. New environmental measurement data, inspection of different materials in use, considerations, modelling and conclusions on the first ventilation measurements and recommendations about the definition of the macroclimate in the shelters are presented. For an optimal preservation, the winter shelters have to be designed and adapted with respect to the material properties of the stone.

Examination of 131I and 137Cs releases during late phase of Fukushima Daiichi NPP accident by using 131I/137Cs ratio of source terms evaluated reversely by WSPEEDI code with environmental monitoring data

ABSTRACTTo investigate what happened in reality during the Fukushima Daiichi Nuclear Power Plant accident, the phenomena within reactor pressure vessel and the discussion of ties with the environmental monitoring measurement are very important. However, the previous study that treats phenomena of the both has not necessarily advanced up to the present time. The source terms predicted by simulation codes such as MELCOR has not yet been consistent with the reverse estimation by WSPEEDI code using environmental measurement data. This study investigated 131I and 137Cs release behaviors during the late phase of the accident to contribute to such examination using the 131I/137Cs ratio of the new source terms predicted by Katata. The 131I release by the gas–liquid partition from the contaminated water in the 1F2 and 1F3 reactor buildings which was pointed out in the previous study was reevaluated using the new source terms. In addition, paying attention to the similarity of the core conditions between the Fukushima accident and the Phébus FPT3 experiment using the B4C control rods, the release of organic iodine (CH3I) during the 1F3 suppression pool venting, formation of CsBO2 and its release behavior were examined which have not yet been sufficiently studied so far.

Long-Term Formaldehyde Emissions from Medium-Density Fiberboard in a Full-Scale Experimental Room: Emission Characteristics and the Effects of Temperature and Humidity.

We studied formaldehyde emissions from the medium-density fiberboard (MDF) in a full-scale experimental room to approximate emissions in actual buildings. Detailed indoor formaldehyde concentrations and temperature and humidity data were obtained for about 29 months. Temperature, relative humidity (RH), and absolute humidity (AH) ranged over -10.9-31.4 °C, 46.5-83.6%, and 1.1-23.1 g/kgair, respectively. Annual cyclical seasonal variations were observed for indoor formaldehyde concentrations and emission rates, exhibiting entirely different characteristics than those in an environmental chamber under constant environmental conditions. The maximum concentration occurred in summer rather than at initial introduction of the material. The concentrations in summer could be a few up to 20 times higher than that in winter, depending on the indoor temperature and humidity conditions. Concentrations decreased by 20-65% in corresponding months of the second year. Indoor formaldehyde concentrations were positively correlated with temperature and AH but were poorly correlated with RH. The combined effects of temperature and AH on formaldehyde emissions from MDF in actual buildings were verified. These detailed long-term experimental results could be used with environmental chamber measurement data to scale up and validate emission models from chambers held at constant conditions to actual buildings.

A First Environmental Burden Of Disease Assessment For Children And Adolescents In Germany

Introduction: Environmental Burden of Disease (EBD) estimates are increasingly used by scientists to inform policy decision-makers about major environmental drivers causing ill-health. Currently no up-to-date national estimates of the EBD are available for Germany and existing estimates have not been generated with current state of the Global Burden of Disease methodology. Especially children and adolescents represent a group strongly vulnerable to environmental hazards. Consequently, the aim of the study is to estimate the EBD for 16 risk factors in children, aged 3-17 years, in Germany. Methods: The study is based on the standardized EBD methodology and its core measure, the disability-adjusted life year (DALY). The current exposure of children and adolescents will be quantified by human biomonitoring and environmental measurement data gathered in the currently ongoing, population-representative German Environmental Survey (GerES 2014-2017). For risk factors with cumulative chronic effects and long lag periods, probabilistic models, based on past trends, will be set up to estimate the future exposure and associated health outcomes. Results: Earlier studies identified particulate matter and second-hand-smoke as important risk factors for the German population. In this study we will update and reevaluate existing estimates and add new information on e.g. ultrafine particles, environmental noise, introduce evidence about newly identified carcinogenic effects of lead and include endocrine disruptors. Further, the study will also evaluate the economic burden caused by particulate matter pollution. Discussion: Even though children and adolescents presently seem to be a quite healthy segment of the society, they are particularly susceptible for the effects of environmental pollutants which can cause disease burden in their future life. The tailored methods and assumptions will shed additional light on the disease burden of one of the most vulnerable population groups.

Participatory noise mapping works! An evaluation of participatory sensing as an alternative to standard techniques for environmental monitoring

Participatory sensing enables a person-centric collection of environmental measurement data with, in principle, high granularity in space and time. In this paper we provide concrete proof that participatory techniques, when implemented properly, can achieve the same accuracy as standard noise mapping techniques. We do this through a citizen science experiment for noise mapping a 1 km2 area in the city of Antwerp using NoiseTube, a participatory sensing framework for monitoring ambient noise. At the technical side, we set up measuring equipment in accordance with official norms insofar as they apply, also carrying out extensive calibration experiments. At the citizen side, we collaborated with up to 13 volunteers from a citizen-led Antwerp-based action group. From the data gathered we construct purely measurement-based noise maps of the target area with error margins comparable to those of official simulation-based noise maps. We also report on a survey evaluating NoiseTube, as a system for participative grassroots noise mapping campaigns, from the user perspective.

RACER

To facilitate access to and use of environmental measurement data, Risk Assessment Corporation has developed a data management system as part of its Risk Analysis, Communication, Evaluation, and Reduction process. The concepts of data consistency are not new, but many data management applications are developed around managing the entire data life cycle, rather than on using the data to reach meaningful conclusions. The RACER process is specifically focused on the efficient use of available data to promote sound decision making. The RACER data management system provides a means of understanding trends in data, comparing data to frequently referenced comparison values, and organizing environmental measurement data for use by other components of the RACER process that evaluate human health impacts. Data transfers to the system can be automated to occur frequently for facilities collecting large volumes of data to achieve a dynamic point of access to measurement data that reflects the most recently available information. Because the RACER process is designed around the most common uses of data, its utility spans a broad range of potential applications, from routine monitoring and reporting to emergency response decision making based on potential human health impacts. Because it is portable and flexible, the elements of the system can be used in any situation where there is a need to efficiently access and interpret environmental measurement data. Its output and functions are equally relevant for small datasets with hundreds of measurements or large and complex datasets with millions of measurements.

MAPPING ENVIRONMENTAL HAZARDS AND BLACK CARBON MEASUREMENTS IN AN IMMIGRANT COMMUNITY

Background and Aims: The Vietnamese population in the US is a rapidly growing immigrant group. This population shows increasing trends for many chronic health problems with increasing number of years in the US, which may be attributed in part to environmental stressors. The objective of this project is to use qualitative and quantitative methods to identify and characterize neighborhood-level environmental hazards for the Vietnamese population in California. Key to this work is the integrated participation and perspective of Vietnamese community members to identify and prioritize elements of their community that potentially impact their health. Methods: Community members (N=35) from two counties in California were recruited and trained to conduct walking street audits of environmental hazards in neighborhoods where they live and work. Each street segment was approximately one city block long. Participants carried GPS devices, collected black carbon measurements using small real-time personal monitors, conducted five-minute car and truck counts and used Photovoice documentary methods. Results: The walking audits were conducted on 144 street segments, of which 45% were in business areas and 55% in residential areas. The mean five-minute truck count was 2 (range: 0 -10) on business streets and 0.3 (range: 0-4) in residential areas. The median level of black carbon was 1.3 µg BC/m3 (range: 0-41). Observational audit survey data highlighted issues around litter and smoking, as well as traffic-related odors and noise. Qualitative data from Photovoice and written comments from auditors reflected concerns around neighborhood safety. Conclusions: We successfully engaged community members in collecting qualitative and quantitative environmental data on their local neighborhoods. Comparisons between these community-collected snapshot data to governmental monitoring data for traffic and black carbon will help inform how well existing secondary data can capture perceived local environmental hazards and how the community-collected data can be used to enhance existing environmental measurement data.

Use of Measurement Data in Evaluating Exposure of Humans and Wildlife to POPs/PBTs

The Stockholm Convention on Persistent Organic Pollutants (POPs) recognized that POPs resist degradation, undergo long-range transport, and accumulate in remote ecosystems. The Stockholm Convention also acknowledged that indigenous communities, particularly in the Arctic, were at risk because of the biomagnification of POPs and contamination of their traditional foods. This recognition was largely based on environmental monitoring data and demonstrates the need to have adequate guidance on data collection and use. Although long-range transport, persistence, and bioaccumulation models are important for screening potential POPs and for assessing human exposure, environmental measurement data are needed to confirm predictions. Indeed the Stockholm Convention (Annex E) requires monitoring data for assessing "exposure in local areas and, in particular, as a result of long-range environmental transport". However, there is relatively little guidance available on the most appropriate environmental measurement approaches, particularly for new candidate POPs, and on how to create a weight of evidence based on such data. We provide guidance on how to assess existing data that have been generated by monitoring programs and individual studies on the exposure of top predators and humans to candidate or potential POPs, as well as considerations for collecting new additional data. Our overall recommendation for assessing exposure in humans and top predators is to use or obtain direct measurements of the compound of concern from a significantly and uniquely exposed population (indigenous populations, remote populations), as well as data demonstrating biomagnification within food webs and time trends if possible. These data must be from the appropriate sample matrix type, collected and analyzed using accepted methodologies, reviewed for quality assurance, and interpreted correctly in order to be used to assess exposure.

A daily harvest prediction model of cherry tomatoes by mining from past averaging data and using topological case-based modeling

A daily harvest prediction model for an individual plant production system is proposed. The model is based on data mining and topological case-based modeling. Environmental measurement data that was logged by an environmental control computer in a greenhouse, daily working hours and daily harvest records were averaged for each period. Each averaged data was correlated with harvest on the object day. The calculated squared correlation values were visualized with the 3D graphs. The graphs helped to understand the relationship between the daily harvest and each factor that influenced the harvest. The model was applied to a greenhouse for producing cherry tomatoes. Four variables, which were harvest in the past, the numeric code of the day of the week, total working hours and daily difference of air temperature, were chosen for developing the predicting model in the data mining process. The chosen data was quantized and placed on the case-base cells in the computer memory. The topological case-based modeling used the principle of continuous mapping to predict the daily harvest. The least error of the predicted yield by the developed model was ±31 kg day −1 (26%) in the greenhouse.

Selecting measures for corporate environmental quality: Examples from TQEM companies

AbstractCompanies undertaking TQEM programs must decide how to measure continuous improvement in the environmental field at the outset of their implementation activities. In the past three years, the leading TQEM companies have made these tough choices and have begun to share their findings with the larger professional community. The author proposes a model for classifying environmental measurement data and presents examples of approaches adopted by TQEM companies.

Toxic Trace Elements Associated with Airborne Particulate Matter: A Review

This article provides a concise review of published literature pertaining to sampling and analytical methodologies, aerometric studies, source identification techniques and modeling activities for the elements arsenic, cadmium, nickel, lead, vanadium, zinc, cobalt, chromium, copper, iron, mercury, manganese, selenium and antimony, and their compounds, associated with airborne particulate matter. Sampling techniques discussed include filtration and inertial separation. Analytical methodologies such as atomic absorption and atomic emission spectrometry, neutron activation analysis, and X-ray fluorescence spectrometry are summarized. Data on atmospheric levels of 14 trace elements are presented in summary form from numerous studies in remote, rural and urban areas, and generally indicate that concentrations measured at rural locations are several orders of magnitude lower than those measured for urban areas. Source identification methodologies are discussed in terms of advantages and disadvantages, and various applications are cited for the following categories: size differentiation, enrichment factors, chemical mass balance, and multivariate models. Provided that reliable trace element data are available for both the source and the receptor, chemical mass balance and multivariate methods can account for up to 80 percent of all sources contributing to the observed ambient air concentration. Wet and dry deposition processes are reviewed and environmental measurement data are provided for each element for remote, rural and urban locations. Both wet and dry deposition fluxes need to be considered for trace elements when estimating the total annual amounts of various trace elements deposited at a particular locale. Global cycles and trace element budgets are introduced in the context of the types of models currently in use. Limitations include inadequate global scale surveys of heavy metal concentrations and the lack of knowledge of sources and/or sinks.

Multi‐phase non‐steady state equilibrium model for evaluation of environmental fate of organic chemicals

A simple mathematical fate model, Multi‐Phase Non‐Steady State Equilibrium Model (MNSEM) is proposed to evaluate distribution, persistence, and concentrations of chemicals in a model environment consisting of air, water, soil and sediment phases. The model is applied to evaluation of environmental fate and concentration of trichloroethylene and 1,4‐dichlorobenzene under generic conditions representative of Japan. Evaluated chemical concentrations in air are within a factor of 3 of average values in Japanese atmosphere, and evaluated concentrations in water, sediment, or fish are greater than an order of magnitude below detection limits in real environments, so that evaluated concentrations are in reasonable agreement with environmental measurement data in Japan. Although MNSEM is not a model for site‐specific evaluation of environmental fate, results suggested that this model is an adequate method to aid in evaluation of fate of chemicals under generic environment conditions. Evaluated concentration‐profi...