Project description:We sequenced two metagenomes from upper sediment layers (0 to 5 and 6 to 10?cm) from the Kanawha River, West Virginia. The watershed includes inputs from the forested Appalachian Mountains, surface coal mining, municipal residues, and extensive chemical manufacturing. The dominant bacterial phyla were Proteobacteria, Bacteriodetes, Firmicutes, Actinobacteria, and Chloroflexi Xenobiotic degradation pathways were present.
Project description:Exposure to indoor air pollution generated from the combustion of solid fuels is a major risk factor for a spectrum of cardiovascular and respiratory diseases, including lung cancer. In China’s rural counties of Xuanwei and Fuyuan, lung cancer rates are among the highest in the country. While the elevated disease risk in this population has been linked to the widespread usage of bituminous (smoky) coal as compared to anthracite (smokeless) coal, the underlying physiologic mechanism that smoky coal induces in comparison to other fuel types is unclear. As we have previously used airway gene-expression profiling to gain molecular insights into the physiologic effects of cigarette smoke, here we profiled the buccal epithelium of residents exposed to the burning of smoky and smokeless coal in order to understand the physiologic effects of solid fuels. Buccal mucosa scrapings were collected from healthy, non-smoking female residents of Xuanwei and Fuyuan counties who burn coal indoors. RNA was isolated and hybridized onto Affymetrix Human gene 1.0 ST GeneChips, capturing the gene-expression response of (n=26) smoky coal users and (n=9) smokeless coal users. 24-hour indoor personal exposure levels (PM2.5, Polycyclic Aromatic Hydrocarbons) were also captured during this sampling period.
Project description:BACKGROUND: Methane oxidizing prokaryotes in marine sediments are believed to function as a methane filter reducing the oceanic contribution to the global methane emission. In the anoxic parts of the sediments, oxidation of methane is accomplished by anaerobic methanotrophic archaea (ANME) living in syntrophy with sulphate reducing bacteria. This anaerobic oxidation of methane is assumed to be a coupling of reversed methanogenesis and dissimilatory sulphate reduction. Where oxygen is available aerobic methanotrophs take part in methane oxidation. In this study, we used metagenomics to characterize the taxonomic and metabolic potential for methane oxidation at the Tonya seep in the Coal Oil Point area, California. Two metagenomes from different sediment depth horizons (0-4 cm and 10-15 cm below sea floor) were sequenced by 454 technology. The metagenomes were analysed to characterize the distribution of aerobic and anaerobic methanotrophic taxa at the two sediment depths. To gain insight into the metabolic potential the metagenomes were searched for marker genes associated with methane oxidation. RESULTS: Blast searches followed by taxonomic binning in MEGAN revealed aerobic methanotrophs of the genus Methylococcus to be overrepresented in the 0-4 cm metagenome compared to the 10-15 cm metagenome. In the 10-15 cm metagenome, ANME of the ANME-1 clade, were identified as the most abundant methanotrophic taxon with 8.6% of the reads. Searches for particulate methane monooxygenase (pmoA) and methyl-coenzyme M reductase (mcrA), marker genes for aerobic and anaerobic oxidation of methane respectively, identified pmoA in the 0-4 cm metagenome as Methylococcaceae related. The mcrA reads from the 10-15 cm horizon were all classified as originating from the ANME-1 clade. CONCLUSIONS: Most of the taxa detected were present in both metagenomes and differences in community structure and corresponding metabolic potential between the two samples were mainly due to abundance differences. The results suggests that the Tonya Seep sediment is a robust methane filter, where taxa presently dominating this process could be replaced by less abundant methanotrophic taxa in case of changed environmental conditions.
Project description:The enrichment of coalbed methane (CBM) and the outburst of gas in a coal mine are closely related to the nanopore structure of coal. The evolutionary characteristics of 12 coal nanopore structures under different natural deformational mechanisms (brittle and ductile deformation) are studied using a scanning electron microscope (SEM) and low-temperature nitrogen adsorption. The results indicate that there are mainly submicropores (2~5 nm) and supermicropores (<2 nm) in ductile deformed coal and mesopores (10~100 nm) and micropores (5~10 nm) in brittle deformed coal. The cumulative pore volume (V) and surface area (S) in brittle deformed coal are smaller than those in ductile deformed coal which indicates more adsorption space for gas. The coal with the smaller pores exhibits a large surface area, and coal with the larger pores exhibits a large volume for a given pore volume. We also found that the relationship between S and V turns from a positive correlation to a negative correlation when S > 4 m(2)/g, with pore sizes <5 nm in ductile deformed coal. The nanopore structure (<100 nm) and its distribution could be affected by macromolecular structure in two ways. Interconversion will occur among the different size nanopores especially in ductile deformed coal.
Project description:Highwall mining (HWM) technology is an efficient method for exploiting residual coal resources in Chinese open-pit coal mines. However, on-site personnel and equipment can be damaged by the instability of the highwall mining residual coal pillars and subsidence of final end-walls. This paper considers the geological conditions of an open-pit mine in Shendong Coal Field (China) in order to prevent overlying rock fall accidents; the Mark-Bieniawski formula and the FLAC3D numerical simulation are used to analyse reasonable coal pillar widths outside and under the road, which were determined to be 1.7 m and 1.3 m, respectively. Using the EBH132 cantilever excavator for remote control mining, the field experiment shows that the recovery ratio of highwall residual coal resources was over 67%; hence, safety, efficiency and high recovery ratio of highwall mining were achieved for the residual coal resources of an open-pit mine.
Project description:Coal was central to the industrial revolution, but in the 20th century it increasingly was superseded by oil and gas. However, in recent years coal again has become the predominant source of global carbon emissions. We show that this trend of rapidly increasing coal-based emissions is not restricted to a few individual countries such as China. Rather, we are witnessing a global renaissance of coal majorly driven by poor, fast-growing countries that increasingly rely on coal to satisfy their growing energy demand. The low price of coal relative to gas and oil has played an important role in accelerating coal consumption since the end of the 1990s. In this article, we show that in the increasingly integrated global coal market the availability of a domestic coal resource does not have a statistically significant impact on the use of coal and related emissions. These findings have important implications for climate change mitigation: If future economic growth of poor countries is fueled mainly by coal, ambitious mitigation targets very likely will become infeasible. Building new coal power plant capacities will lead to lock-in effects for the next few decades. If that lock-in is to be avoided, international climate policy must find ways to offer viable alternatives to coal for developing countries.
Project description:Coal combustion by-products (CCPs) (i.e. fly (FA) and bottom (BA) ashes) generated by power plants contain heavy metals. This research presents leaching properties of coal ashes (FA and BA) collected from Jimah coal-fired power station, Port Dickson, Negeri Sembilan using USEPA standard methods namely toxicity characteristic leaching procedure (TCLP), and synthetic precipitation leaching procedure (SPLP). Heavy metals like lead (Pb), zinc (Zn), copper (Cu) and arsenic (As) were quantified using atomic absorption spectrometer (AAS). The leached of heavy metals fluxes were Cu < Zn < Pb < As. As leached the most whilst indicating of possible contamination from As. Overall, the ranges of leached concentration were adhered to permissible limits of hazardous waste criteria for metal (Pb and As) and industrial effluent (Zn and Cu). The presented data has potential reuse as reference for the coal ash concrete mixed design application in construction industries.
Project description:Coal ash, generated from coal combustion, is composed of small particles containing metals and other elements, such as metalloids. Coal ash is stored in open-air impoundments, frequently near communities. The objective of this study was to evaluate the prevalence of health and sleep problems in children living near coal ash and compare these prevalences to children not living near coal ash. In 2013 to 2014, we conducted a cross-sectional survey in a community adjacent to coal ash storage sites and a community not exposed to coal ash. Overall, 111 children who lived near coal ash were in the study; 55.9% (62) were males, 44.1% (49) were females, and the mean age was 10.3 years (SD = 3.9). Descriptive statistics and logistic regression were used to compare the prevalence of health and sleep problems. Attention-deficit hyperactivity disorder (P = .02), gastrointestinal problems (P = .01), difficulty falling asleep (P = .007), frequent night awakenings (P < .001), teeth grinding (P = .03), and complaint of leg cramps (P < .001) were significantly greater in the children living near coal ash. When adjusting for covariates, the odds of allergies excluding asthma, attention-deficit hyperactivity disorder, gastrointestinal problems, difficulty falling asleep, frequent night awakenings, sleep talking, and complaint of leg cramps were greater in children living near coal ash compared to children not living near coal ash (nonexposed). Several components of coal ash, such as heavy metals like lead, mercury, and arsenic, may be associated with health and sleep problems in children. More research is needed to investigate this relationship.
Project description:The Xuanwei area is a hot spot of lung adenocarcinoma in females in China, which is strongly associated with the consumption of local smoky coal. Comprehensive characterization of its genomic and immunological landscapes is crucial for cancer prevention and the development of precision therapy. Here, we report extensive genomic, transcriptomic, and immunological profiles of 117 Xuanwei female lung adenocarcinoma (XWFA), comprising 112 pairs of tumour-normal whole-exon sequencing (WES) profiles and 33 normal and 115 tumour mRNA-seq profiles. Overall design: To investigate the molecular mechanism underlying lung cancer we established rat lung cancer model induced with smoky coal.
Project description:The significance of coal in the world economy remains unquestionable for decades. It is also expected to be the dominant fossil fuel in the foreseeable future. The increased awareness of sustainable development reflected in the relevant regulations implies, however, the need for the development and implementation of clean coal technologies on the one hand, and adequate analytical tools on the other. The paper presents the application of the quantitative Partial Least Squares method in modeling the concentrations of trace elements (As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Rb, Sr, V and Zn) in hard coal based on the physical and chemical parameters of coal, and coal ash components. The study was focused on trace elements potentially hazardous to the environment when emitted from coal processing systems. The studied data included 24 parameters determined for 132 coal samples provided by 17 coal mines of the Upper Silesian Coal Basin, Poland. Since the data set contained outliers, the construction of robust Partial Least Squares models for contaminated data set and the correct identification of outlying objects based on the robust scales were required. These enabled the development of the correct Partial Least Squares models, characterized by good fit and prediction abilities. The root mean square error was below 10% for all except for one the final Partial Least Squares models constructed, and the prediction error (root mean square error of cross-validation) exceeded 10% only for three models constructed. The study is of both cognitive and applicative importance. It presents the unique application of the chemometric methods of data exploration in modeling the content of trace elements in coal. In this way it contributes to the development of useful tools of coal quality assessment.