scholarly journals Indicators of Electric Power Instability from Satellite Observed Nighttime Lights

2020 ◽  
Vol 12 (19) ◽  
pp. 3194
Author(s):  
Christopher D. Elvidge ◽  
Feng-Chi Hsu ◽  
Mikhail Zhizhin ◽  
Tilottama Ghosh ◽  
Jay Taneja ◽  
...  
Keyword(s):  
Electric Power ◽  
Infrared Imaging ◽  
Developing Economies ◽  
Population Level ◽  
Data Availability ◽  
Residual Variance ◽  
Spatial And Temporal Patterns ◽  
Northern India ◽  
Temporal Profiles ◽  
Power Instability

Electric power services are fundamental to prosperity and economic development. Disruptions in the electricity power service can range from minutes to days. Such events are common in many developing economies, where the power generation and delivery infrastructure is often insufficient to meet demand and operational challenges. Yet, despite the large impacts, poor data availability has meant that relatively little is known about the spatial and temporal patterns of electric power reliability. Here, we explore the expressions of electric power instability recorded in temporal profiles of satellite observed surface lighting collected by the Visible Infrared Imaging Radiometer Suite (VIIRS) low light imaging day/night band (DNB). The nightly temporal profiles span from 2012 through to mid-2020 and contain more than 3000 observations, each from a total of 16 test sites from Africa, Asia, and North America. We present our findings in terms of various novel indicators. The preprocessing steps included radiometric adjustments designed to reduce variance due to the view angle and lunar illumination differences. The residual variance after the radiometric adjustments suggests the presence of a previously unidentified source of variability in the DNB observations of surface lighting. We believe that the short dwell time of the DNB pixel collections results in the vast under-sampling of the alternating current lighting flicker cycles. We tested 12 separate indices and looked for evidence of power instability. The key characteristic of lights in cities with developing electric power services is that they are quite dim, typically 5 to 10 times dimmer for the same population level as in Organization for Economic Co-operation and Development (OECD) countries. In fact, the radiances for developing cities are just slightly above the detection limit, in the range of 1 to 10 nanowatts. The clearest indicator for power loss is the percent outage. Indicators for supply adequacy include the radiance per person and the percent of population with detectable lights. The best indicator for load-shedding is annual cycling, which was found in more than half of the grid cells in two Northern India cities. Cities with frequent upward or downward radiance spikes can have anomalously high levels of variance, skew, and kurtosis. A final observation is that, barring war or catastrophic events, the year-on-year changes in lighting are quite small. Most cities are either largely stable over time, or are gradually increasing in indices such as the mean, variance, and lift, indicating a trajectory that proceeds across multiple years.

scholarly journals Close-Range Photogrammetry and Infrared Imaging for Non-Invasive Honeybee Hive Population Assessment

2018 ◽  
Vol 7 (9) ◽  
pp. 350 ◽  
Author(s):  
Luis López-Fernández ◽  
Susana Lagüela ◽  
Pablo Rodríguez-Gonzálvez ◽  
José Martín-Jiménez ◽  
Diego González-Aguilera
Keyword(s):  
Computer Vision ◽  
Infrared Imaging ◽  
Imaging Techniques ◽  
Population Level ◽  
Non Invasive ◽  
Close Range Photogrammetry ◽  
3D Geometry ◽  
Thermographic Imaging ◽  
Close Range ◽  
Bee Colonies

Close-range photogrammetry and thermographic imaging techniques are used for the acquisition of all the data needed for the non-invasive assessment of a honeybee hive population. Temperature values complemented with precise 3D geometry generated using novel close-range photogrammetric and computer vision algorithms are used for the computation of the inner beehive temperature at each point of its surface. The methodology was validated through its application to three reference beehives with different population levels. The temperatures reached by the exterior surfaces of the hives showed a direct correlation with the population level. In addition, the knowledge of the 3D reality of the hives and the position of each temperature value allowed the positioning of the bee colonies without the need to open the hives. This way, the state of honeybee hives regarding the growth of population can be estimated without disturbing its natural development.

scholarly journals Data safe havens to combine health and genomic data: benefits and challenges

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Kerina H Jones ◽  
Arron S Lacey ◽  
Brian L Perkins ◽  
Mark I Rees
Keyword(s):  
Association Studies ◽  
Genomic Data ◽  
Population Level ◽  
Data Availability ◽  
Genome Wide Association Studies ◽  
Related Data ◽  
Research Areas ◽  
Individual Privacy ◽  
Access Controls ◽  
Health Related

ABSTRACTObjectivesData safe havens can bring together and combine a rich array of anonymised person-based data for research and policy evaluation within a secure setting. To date, the majority of available datasets have been structured micro-data derived from routine health-related records. Possibilities are opening up for the greater reuse of genomic data such as Genome Wide Association studies (GWAS) and Whole Exome/Genome Sequencing (WES or WGS). However, there are considerable challenges to be addressed if the benefits of using these data in combination with health-related data are to be realized safely. ApproachWe explore the benefits and challenges of using genomic datasets with health-related data, and using the Secure Anonymised Information Linkage (SAIL) system as a case study, the implications and way forward for Data Safe Havens in seeking to incorporate genomic data for use with health-related data. ResultsThe benefits of using GWAS, WES and WGS data in conjunction with health-related data include the potential to explore genetics at a population level and open up novel research areas. These include the ability to increasingly stratify and personalize how medical indications are detected and treated through precision medicine by understanding rare conditions and adding socioeconomic and environmental context to genomic data. Among the challenges are: data availability, computing capacity, technical solutions, legal and regulatory frameworks, public perceptions, individual privacy and organizational risk. Many of the challenges within these areas are common to person-based data in general, and often Data Safe Havens have been designed to address these. But there are also aspects of these challenges, and other challenges, specific to genomic data. These include issues due to the unknown clinical significance of genomic information now or in the future, with corresponding risks for privacy and impact on individuals. ConclusionGenomic data sets contain vast amounts of valuable information, some of which is currently undefined, but which may have direct bearing on individual health at some point. The use of these data in combination with health-related data has the potential to bring great benefits, better clinical trial stratification, epidemiology project design and clinical improvements. It is, therefore, essential that such data are surrounded by a properly-designed, robust governance framework including technical and procedural access controls that enable the data to be used safely.

scholarly journals The Relationship Between Public Expenditures, Total Factor Productivity and Economic Growth: A Panel Data Analysis

2021 ◽  
Author(s):  
Remzi Can Yılmaz ◽  
Ahmet Rutkay Ardoğan
Keyword(s):  
Economic Growth ◽  
Total Factor Productivity ◽  
Developing Economies ◽  
Panel Data Analysis ◽  
Statistical Significance ◽  
Data Availability ◽  
Public Expenditures ◽  
Annual Data ◽  
Factor Productivity ◽  
The Relationship

According to the economics literature, there are two main sources of economic growth. While the first of the resources is the accumulation of production factors, the other is the part of the output that cannot be explained by the amount of input used in production, in other words, the total factor productivity. The level of total factor productivity is measured according to how efficiently the inputs are used in the production process. In this study, the hypothesis that public spending affects real economic growth through total productivity is investigated. In the first stage, whether the changes in public expenditures affect the total factor productivity or not; if it does, to what extent and in what direction it has been tried to be revealed. In the second stage, the effect of total factor productivity on economic growth was examined and the statistical significance, direction and extent of the relationship between variables were investigated. Annual data were used in the study and the year range is 2000-2017. The sampling economies were selected according to data availability, and there are a total of 20 developed and developing economies. Research was conducted using multiple panel regression analysis. According to the findings, the relationship between public expenditures and total factor productivity is statistically significant. An increase in public expenditures reduces the total factor productivity. The relationship between total factor productivity and economic growth is statistically significant, and an increase in total factor productivity also increases economic growth. An increase in public expenditures affects economic growth negatively by reducing the total factor productivity.

scholarly journals Estimating Rural Electric Power Consumption Using NPP-VIIRS Night-Time Light, Toponym and POI Data in Ethnic Minority Areas of China

2020 ◽  
Vol 12 (17) ◽  
pp. 2836
Author(s):  
Fei Zhao ◽  
Jieyu Ding ◽  
Sujin Zhang ◽  
Guize Luan ◽  
Lu Song ◽  
...  
Keyword(s):  
Power Consumption ◽  
Ethnic Minority ◽  
Electric Power ◽  
Rural Areas ◽  
Infrared Imaging ◽  
Electricity Consumption ◽  
Electric Power Consumption ◽  
Average Error ◽  
Night Time ◽  
Spatial Differences

Aiming at the problem that the estimation of electric power consumption (EPC) by using night-time light (NTL) data is mostly concentrated in large areas, a method for estimating EPC in rural areas is proposed. Rural electric power consumption (REPC) is a key indicator of the national socio-economic development. Despite an improved quality of life in rural areas, there is still a big gap between electricity consumption between rural residents and urban residents in China. The experiment takes REPC as the research target, selects Dehong (DH) Dai Jingpo Autonomous Prefecture of Yunnan Province as an example, and uses the NTL data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) carried by the Suomi National Polar-orbiting Partnership (NPP) Satellite from 2012 to 2017, toponym and points-of-interest (POI) data as the main data source. By performing kernel density estimation to extract the urban center and rural area boundaries in the prefecture, and combining the county-level boundary data and electric power data, a linear regression model of the total rural NTL intensity and REPC is estimated. Finally, according to the model, the EPC in ethnic minority rural areas is estimated at a 1-km spatial resolution. The results show that the NPP-REPC model can simulate REPC within a small average error (17.8%). Additionally, there are distinct spatial differences of REPC in ethnic minority areas.

A comparison of methods for determining proximate carbon fractions of forest litter

1990 ◽  
Vol 20 (2) ◽  
pp. 166-171 ◽  
Author(s):  
Michael G. Ryan ◽  
Jerry M. Melillo ◽  
Andrea Ricca
Keyword(s):  
Chemical Analysis ◽  
Forest Products ◽  
Forest Litter ◽  
Data Availability ◽  
Residual Variance ◽  
Comparison Of Methods ◽  
Predictive Equations ◽  
Carbon Fractions ◽  
Decomposition Models ◽  
The Relationship

Ten forest litters with decomposition state varying from 16.6 to 100% weight remaining were partitioned into sub-samples; each subsample was analyzed for proximate carbon fractions using one of two chemical analysis procedures (forage fiber and forest products analyses). Proximate carbon fractions from the simpler forage fiber techniques accurately estimated extractives, cellulose, lignin, and acid-hydrolyzed carbohydrates (R2 > 0.83) determined by the more complex forest products analyses. Decomposition state accounted for most of the residual variance and significantly improved predictive equations for lignin and extractives. The relationship between proximate carbon fractions from the different techniques also varied somewhat among wood, hardwood leaves, and conifer leaves; however, variations were minor relative to the overall trend. Equations developed can be used to extend data availability for developing and validating decomposition models.

scholarly journals ANALYSIS OF NO<sub>2</sub> TROPOSPHERIC COLUMN AMOUNT AT AIRPORTS IN MALAYSIA BEFORE AND DURING COVID-19 PANDEMIC USING SENTINEL-5P TROPOMI DATA

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 399-403
Author(s):  
K. D. Kanniah ◽  
N. A. F. Kamarul Zaman ◽  
K. Perumal
Keyword(s):  
Climate Change ◽  
Human Health ◽  
Urban Areas ◽  
Air Pollutants ◽  
Temporal Variations ◽  
Data Availability ◽  
Spatial And Temporal Patterns ◽  
Movement Restriction ◽  
Motorized Vehicles ◽  
The Impact

Abstract. Air pollution is a serious environmental and health issue in Malaysia due to the recent urbanization processes. The main sources of air pollutants are motorized vehicles in urban areas and airports and industrial activities. At the airports, NO2 is the main pollutant of concern besides aerosols particles, yet gap in data availability prevent studies to describe their patterns and quantify their effects on human health and climate change. In this study NO2 data from TROPOMI sensor on board Sentinel 5-P satellite was used to characterize the spatial and temporal patterns of NO2 tropospheric column amounts at major airports in Malaysia. The results demonstrate that NO2 amounts from aircrafts and ground traffic activities are generally higher and/or similar to the amounts found in urban areas. Total tropospheric column amounts of NO2 during the movement restriction imposed due to Covid-19 pandemic between March and April 2020 was approximately 50% lower the total emission during the same period in 2019 (representing a business as usual period). Assessing the spatial pattern and temporal variations in NO2 (both surface and total vertical profile) is important for monitoring the impact of air pollutants on climate change and human health in Malaysia.

scholarly journals Dynamic Anthropogenic activitieS impacting Heat emissions (DASHv1.0): Development and evaluation

2020 ◽  
Author(s):  
Isabella Capel-Timms ◽  
Stefán Thor Smith ◽  
Ting Sun ◽  
Sue Grimmond
Keyword(s):  
Land Surface ◽  
Urban Form ◽  
Anthropogenic Activities ◽  
Heat Fluxes ◽  
Outdoor Environment ◽  
Data Availability ◽  
Anthropogenic Heat ◽  
Surface Model ◽  
Spatial And Temporal Patterns ◽  
Top Down

Abstract. Thermal emissions or anthropogenic heat fluxes (QF) from human activities impact the local and larger scales urban climate. DASH considers both urban form and function in simulating QF by use of an agent-based structure that includes behavioural characteristics of city populations. This allows social practices to drive the calculation of QF as occupants move, varying by day type, demographic, location, activity, socio-economic factors and in response to environmental conditions. The spatial resolution depends on data availability. DASH has simple transport and building energy models to allow simulation of dynamic vehicle use, occupancy and heating/cooling demand, with subsequent release of energy to the outdoor environment through the building fabric. Building stock variations are captured using archetypes. Evaluation of DASH in Greater London for various periods in 2015 uses a top-down inventory model (GQF) and national energy consumption statistics. DASH reproduces the expected spatial and temporal patterns of QF but the annual average is smaller than published energy data. Overall the model generally performs well, including for domestic appliance energy use against top down model results. DASH could be coupled to an urban land surface model and/or used offline for developing coefficients for simpler/faster models.

Crisis and Human Biology

2015 ◽  
pp. 51-69 ◽  
Author(s):  
Prashant Bharadwaj ◽  
Tom Vogl
Keyword(s):  
Social Economic ◽  
Population Level ◽  
Crisis Response ◽  
Data Availability ◽  
Human Biology ◽  
Negative Events ◽  
Poor Countries ◽  
Beneficial Effects ◽  
Environmental Disasters ◽  
Biological Outcomes

This chapter reviews the literature on the effects of aggregate crises on human biological outcomes. The crises considered are acute, severe, and unexpected negative events occurring at the population level: recessions, famines, epidemics, natural and environmental disasters, and wars. A review of the literature suggests that the effects of aggregate crises on human biology are pervasive and long-lasting. More broadly, however, the literature highlights the lasting effects that social, economic, political, environmental, and pathological crises have on the human body. Children, who are never complicit in creating crises, carry the burden of exposure for the rest of their lives. Although advances in methodology and data availability have allowed researchers to uncover these nuanced but powerful effects, much work remains in improving crisis response, especially in poor countries. Such improvements would have beneficial effects long after the acute period of a crisis subsides, on outcomes far beyond its most obvious sequelae.

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