DEVELOPMENT OF UNIVARIATE AND MULTIVARIATE FORECASTING MODELS FOR METHANE GAS EMISSIONS IN UNDERGROUND COAL MINES

Methane gas management continues to be a challenge concerning underground coal mine safety and productivity worldwide despite the extraordinary effort of the mining industry, governmental agencies, and academia to develop new technologies to monitor and control methane gas emissions more efficiently. The risk of hazardous methane gas concentrations in underground environments cannot be underestimated. Statistical data for the last 100 years indicate that around 80% of the accidents and 90% of the fatalities in the underground coal mining industry in the US were related to methane gas explosions. Modern underground mine operations monitor and evaluate atmospheric parameters such as barometric pressure, temperature, gas concentrations, and ventilation parameters (e.g., fan performance and airflow) by means of Automated Atmospheric Monitoring Systems, which use sensors that collect a massive amount of data implemented by mine operators to make decisions concerning mine safety and operate ventilation systems more effectively. In addition, however, some of these data can be statistically studied to develop forecast models to help improve the safety and health parameters of underground coal mining operations. The research presented in this dissertation investigates potential correlations between methane gas concentrations and independent variables such as barometric pressure and coal production rate to build reliable forecasting models capable of predicting future concentrations of methane gas, mainly based on time series data collected by the Atmospheric Monitoring System of three active underground coal mining operations in the eastern US and weather data retrieved from public weather stations in the proximity of the case studies. The mine and weather data were stored and pre-processed using an Atmospheric Monitoring Analysis and Database Management system explicitly designed to manage Atmospheric Monitoring Systems data. Furthermore, various statistical techniques were implemented to assess the potential association (e.g., autocorrelation and cross-correlation) between methane gas concentration time series and the independent variables. Such associations were employed to develop univariate and multivariate forecasting models for methane gas emissions in underground coal mines. Finally, the optimal model is selected using the Akaike Information Criterion, and the results obtained from the different forecast approaches (univariate and multivariate) are compared using cross-validation metrics to determine the best model. It was concluded that the ARIMA, VAR, and ARIMAX methane gas forecasting methodologies proposed in this research can accurately predict methane gas concentrations in underground coal mines operations. The methane gas forecasted from the models matched the validation data consistently, and their linear correlation was positive and strong in most cases. In addition, the 95% confidence interval consistently captured the forecast and validation data

DEVELOPMENT OF UNIVARIATE AND MULTIVARIATE FORECASTING MODELS FOR METHANE GAS EMISSIONS IN UNDERGROUND COAL MINES

Methane gas management continues to be a challenge concerning underground coal mine safety and productivity worldwide despite the extraordinary effort of the mining industry, governmental agencies, and academia to develop new technologies to monitor and control methane gas emissions more efficiently. The risk of hazardous methane gas concentrations in underground environments cannot be underestimated. Statistical data for the last 100 years indicate that around 80% of the accidents and 90% of the fatalities in the underground coal mining industry in the US were related to methane gas explosions. Modern underground mine operations monitor and evaluate atmospheric parameters such as barometric pressure, temperature, gas concentrations, and ventilation parameters (e.g., fan performance and airflow) by means of Automated Atmospheric Monitoring Systems, which use sensors that collect a massive amount of data implemented by mine operators to make decisions concerning mine safety and operate ventilation systems more effectively. In addition, however, some of these data can be statistically studied to develop forecast models to help improve the safety and health parameters of underground coal mining operations. The research presented in this dissertation investigates potential correlations between methane gas concentrations and independent variables such as barometric pressure and coal production rate to build reliable forecasting models capable of predicting future concentrations of methane gas, mainly based on time series data collected by the Atmospheric Monitoring System of three active underground coal mining operations in the eastern US and weather data retrieved from public weather stations in the proximity of the case studies. The mine and weather data were stored and pre-processed using an Atmospheric Monitoring Analysis and Database Management system explicitly designed to manage Atmospheric Monitoring Systems data. Furthermore, various statistical techniques were implemented to assess the potential association (e.g., autocorrelation and cross-correlation) between methane gas concentration time series and the independent variables. Such associations were employed to develop univariate and multivariate forecasting models for methane gas emissions in underground coal mines. Finally, the optimal model is selected using the Akaike Information Criterion, and the results obtained from the different forecast approaches (univariate and multivariate) are compared using cross-validation metrics to determine the best model. It was concluded that the ARIMA, VAR, and ARIMAX methane gas forecasting methodologies proposed in this research can accurately predict methane gas concentrations in underground coal mines operations. The methane gas forecasted from the models matched the validation data consistently, and their linear correlation was positive and strong in most cases. In addition, the 95% confidence interval consistently captured the forecast and validation data

Earth Resources: A continuing bibliography with indexes, issue 13

This bibliography lists 524 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1977 and March 1977. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Characterization of atmospheric pollution dynamics in Spain by means of air quality modelling

Atmospheric pollution causes large impacts on human health and societal economic interests and it is a threat for the ecosystems and the climate of the Earth. Improving the understanding of pollution dynamics is necessary to desing efficient air quality strategies that reduce the impacts of air pollution. This Ph.D. Thesis identifies the typical atmospheric conditions at synoptic scale that affect the Iberian Peninsula (IP) and uses them to explain the dynamics of the most relevant gaseous pollutants in Spain (nitrogen dioxide NO2, sulphur dioxide SO2, and ozone O3) by means of air quality modelling. Circulation type classifications (CTC) summarise the continuum of atmospheric circulation into a discrete number of typical circulation types (CTs). For the 1983-2012 climatic period, a CTC is derived to be useful in the characterization of air quality dynamics over the IP. Sensitivity tests to classification techniques (principal components, correlation analysis, clustering) and other factors affecting the CTC (temporal and spatial resolution, domain size, etc.) are performed to objectivize the choice of the automatic set-up that maximizes its quality. The six identified CTs -described in terms of frequency, persistence, transitions, and location of pressure systems- are consistent with CTs found in the literature. The temporal stability of the CTC, evaluated following a cross-validation process that compares the results of the climatic and yearly CTs, leads to the identification of a representative year (2012). A representative day for each CT in 2012 is identified using an objective score that minimizes the differences of the daily and the average surface pressure CT grid. The study of NO2, SO2, and O3 dynamics performed on the representative day of each CT focuses on the biggest Spanish urban areas (Madrid and Barcelona) and heavy industrial/electricity-generation areas such as Asturias (northern Spain) and the Algeciras bay (southern Spain). The state-of-the-art CALIOPE Air Quality Forecast System (CALIOPE-AQFS) that provides high-resolution data on emissions, meteorology, and pollutant concentration over Spain is the main tool used in the characterisation of pollution dynamics. The modelling system is also used to quantify the contribution of specific sources of pollutants -coal-fired power plants and on-road transport- by means of a brute-force approach and an emission-based source apportionment, respectively. The CTs control the transport patterns of SO2/NO2/O3 in Spanish continental and Atlantic areas, whereas in Mediterranean coastal areas and over complex-terrains a combination of synoptic and mesoscale dynamics (sea-land and mountain-valley breezes) explains the pollutant concentration patterns. The power plants' contribution to surface concentration (up to 55 µgSO2 m-3 and 32 µgNO2 m-3) occurs mainly close to the source (< 20 km) related to vertical diffusion when the emission is injected within the planetary boundary layer. However, the SO2/NO2 plumes can reach distances higher than 250 km. The daily maximum O3 concentration attributed to the on-road transport emissions from Madrid and Barcelona contribute up to 24% and 8% to total O3 concentration, respectively, but it is particularly significant (up to 80-100 µg m-3 in an hour) to the O3 concentration peak during the central hours of the day in April-September. The long-range transport of O3 to the IP is controlled by the CTs and its concentration is very significant in the area of influence of Madrid and Barcelona, particularly under cold CTs (70-96%). This Ph.D. Thesis has proven that CALIOPE-AQFS (1) is useful to characterise the 3-D dynamics of primary and secondary pollutants in Spain under typical CTs; (2) is able to attribute and quantify air pollution to its sources via brute force and source apportionment; and (3) has the potential to help in the design of specific, science-based abatement strategies that minimize air pollution impacts.La contaminación atmosférica genera perjuicios en la salud humana, en los intereses económicos de la sociedad y constituye una amenaza para los ecosistemas y el clima de la Tierra. Avanzar en la comprensión de la dinámica de la contaminación facilita el diseño de estrategias de calidad del aire que reduzcan sus impactos. Esta Tesis Doctoral identifica objetivamente patrones típicos de circulación atmosférica (PT) que afectan a la Península Ibérica (PI) a escala sinóptica para explicar la dinámica de los principales contaminantes gaseosos en España (dióxido de nitrógeno NO2, dióxido de azufre SO2 y ozono O3) mediante modelización de la calidad del aire. Las clasificaciones sinópticas (CS) discretizan el continuo de la circulación atmosférica en un catálogo de PT. Para el período climático 1983-2012, se establece una CS útil para el estudio de la dinámica de la contaminación atmosférica en la PI. Tests de sensibilidad para técnicas automáticas de clasificación (análisis de componentes principales, de correlación y clustering) y para otros factores que afectan a la CS (resolución temporal y espacial, tamaño del dominio, etc.) objetivizan la elección de la configuración que maximiza su calidad. Los seis PT identificados - descritos en términos de frecuencia, persistencia, transiciones y ubicación de los sistemas de presión - son consistentes con la literatura. La evaluación de la estabilidad temporal de la clasificación, mediante un proceso de validación cruzada que compara los PT climáticos con PT identificados en CS anuales, permite identificar un año representativo (2012). Un día representativo de cada PT es elegido gracias a un algoritmo que minimiza las diferencias de la malla de presiones diaria respecto de la del PT promedio. El estudio de la dinámica de NO2, SO2 y O3 se realiza en el día representativo de cada PT focalizando en las principales áreas urbanas de España (Madrid y Barcelona) y en importantes áreas industriales y/o de generación eléctrica (Asturias, bahía de Algeciras). El sistema de CALIdad del aire OPeracional para España (CALIOPE) que proporciona datos de alta resolución sobre emisiones, meteorología y concentración de contaminantes es la principal herramienta utilizada en el estudio. CALIOPE permite cuantificar la contribución de determinadas fuentes de emisión, centrales térmicas de carbón y transporte rodado, mediante un enfoque de fuerza bruta y de asignación de fuentes, respectivamente. Los PT controlan el transporte de SO2/NO2/O3 en áreas atlánticas y continentales de España mientras que en zonas costeras mediterráneas y/o de topografía compleja, una combinación de procesos sinópticos y de mesoescala (brisas marinas y de valle) explica los patrones de contaminación. La contribución de SO2 y NO2 de las centrales térmicas a la concentración en superficie (hasta 55 µg m-3 y 32 µg m-3, respectivamente) se produce principalmente cerca de la fuente (<20 km) por difusión vertical de la emisión cuando ésta se inyecta en la capa límite planetaria. Sin embargo, los penachos de SO2/NO2 pueden alcanzar distancias superiores a los 250 km. La contribución máxima diaria de O3 atribuido a emisiones del transporte rodado de Madrid y Barcelona alcanza el 24% y el 8%, respectivamente pero es particularmente significativa (hasta 80-100 µg m-3 en una hora) a mediodía durante el pico de concentración de O3. El transporte a larga distancia de O3 hacia la PI es controlado por los PT y su contribución es muy importante en el área de influencia de Madrid y Barcelona, en particular bajo los PT fríos (70-96%). Esta Tesis Doctoral ha demostrado que CALIOPE es (1) útil para caracterizar la dinámica 3-D de contaminantes primarios y secundarios en España bajo diferentes PT; (2) capaz de atribuir y cuantificar la contaminación a sus fuentes a través de fuerza bruta y atribución de fuentes; y (3) potencialmente útil en el diseño de estrategias de mitigación específicas que minimicen los impactos de la contaminación atmosférica.Postprint (published version

Planet Earth 2011

The failure of the UN climate change summit in Copenhagen in December 2009 to effectively reach a global agreement on emission reduction targets, led many within the developing world to view this as a reversal of the Kyoto Protocol and an attempt by the developed nations to shirk out of their responsibility for climate change. The issue of global warming has been at the top of the political agenda for a number of years and has become even more pressing with the rapid industrialization taking place in China and India. This book looks at the effects of climate change throughout different regions of the world and discusses to what extent cleantech and environmental initiatives such as the destruction of fluorinated greenhouse gases, biofuels, and the role of plant breeding and biotechnology. The book concludes with an insight into the socio-religious impact that global warming has, citing Christianity and Islam

Ecological Genetics of Stipa pulchra in Environmental Restoration

Ecological restoration has become a large enterprise driven by regulatory policies and by public and private initiatives. Regulatory agencies and ecologists call for use of propagules that are adapted to project sites, compatible with other species, and genetically diverse. This project uses a native California grass, Stipa pulchra, to ask whether the cost-management practice of collecting seeds from dense stands of target species can have unintended selective effects on species used in restoration. Absolute cover, standing biomass, species composition, and S. pulchra density and culm count were recorded on plots in three central California sites. S. pulchra seeds from these plots were sown in pots allocated to two watering groups and three temporal blocks. Pot-study plants grown from seed collected from plots with greater absolute cover and S. pulchra density had significantly higher basal diameters, tiller counts, and root: shoot ratios. Plants derived from less-competitive plots reproduced earlier and gave rise to more culms. These results indicate that distribution of S. pulchra genoypes in the field may reflect a competition: colonization pattern, with more fecund S. pulchra plants inhabiting less-competitive patches than those occupied by their more-competitive conspecifics. Other aspects of pot-study plant growth appeared to reflect background vegetation of the field plots. Although plants grown from seeds collected at the three sites were significantly different, there was no evidence that ecological distance reflected geographic distance. Plants receiving more water had relatively greater aboveground growth and lower root: shoot ratios. Statistical interactions of blocking and watering treatments with site may reflect plant adaptation to climate and soil at the various sites. Implications of these results apply to environmental restoration and extend to ecological research, where nonrandomly collected propagules are often used to represent genetic characteristics of entire populations

Spatio-temporal correlation of extreme climate indices and river flood discharges

The occurrence of floods is strongly related to specific climatic conditions that favor extreme precipitation events. Although the impact of precipitation and temperature patterns on river flows is a well discussed topic in hydrology, few studies have focused on the rainfall and temperature extremes in their relation with peak discharges. This work presents a comparative analysis of Climate Change Indices (ETCCDI) annual time series, calculated using the NorthWestern Italy Optimal Interpolation (NWIOI) dataset, and annual maximum flows in the Piedmont Region. The Spearman’s rank correlation was used to determine which indices are temporally correlated with peak discharges, allowing to hypothesize the main physical processes involved in the production of floods. The correlation hypothesis was verified with the Spearman’s rank correlation test, considering a Student’s t-distribution with a 5% significance level. Moreover, the influence of climate variability on the tendency of annual maximum discharges was examined by correlating trends of climate indices with trends of the discharge series. These were calculated using the Theil-Sen slope estimator and tested with the Mann-Kendall test at the 5% significance level. The results highlight that while extreme precipitation indices are highly correlated with extreme discharges at the annual timescale, the interannual changes of extreme discharges may be better explained by the interannual changes of the total annual precipitation. This suggests that projections of the annual precipitation may be used as covariates for non-stationary flood frequency analysis