300 research outputs found

    Co-combustion of sewage sludge with wood/coal in a circulating fluidised bed boiler - A study of NO and N2O emissions

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    Reduction of emissions of NO and N2O from co-combustion of wet or dried sewage sludge with coal or wood is investigated. This is motivated by the high nitrogen content in sewage sludge that may give rise to high emissions. An advanced air-staging method for combustion in circulating fluidised bed is applied. It is shown that with fluidised bed combustion the emissions are low as long as the sludge fraction is not too high (say, less than 25%), and the conversion of fuel nitrogen to NO or N2O is only a few percent. However, air staging as such is not efficient for high volatile fuels, and any air supply method can be applied in such a case, in contrast to combustion of coal, when the air supply arrangement has a decisive influence

    Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits

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    Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma

    Co-firing of biomass and other wastes in fluidised bed systems

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    A project on co-firing in large-scale power plants burning coal is currently funded by the European Commission. It is called COPOWER. The project involves 10 organisations from 6 countries. The project involves combustion studies over the full spectrum of equipment size, ranging from small laboratory-scale reactors and pilot plants, to investigate fundamentals and operating parameters, to proving trials on a commercial power plant in Duisburg. The power plant uses a circulating fluidized bed boiler. The results to be obtained are to be compared as function of scale-up. There are two different coals, 3 types of biomass and 2 kinds of waste materials are to be used for blending with coal for co-firing tests. The baseline values are obtained during a campaign of one month at the power station and the results are used for comparison with those to be obtained in other units of various sizes. Future tests will be implemented with the objective to achieve improvement on baseline values. The fuels to be used are already characterized. There are ongoing studies to determine reactivities of fuels and chars produced from the fuels. Reactivities are determined not only for individual fuels but also for blends to be used. Presently pilot-scale combustion tests are also undertaken to study the effect of blending coal with different types of biomass and waste materials. The potential for synergy to improve combustion is investigated. Early results will be reported in the Conference. Simultaneously, studies to verify the availability of biomass and waste materials in Portugal, Turkey and Italy have been undertaken. Techno-economic barriers for the future use of biomass and other waste materials are identified. The potential of using these materials in coal fired power stations has been assessed. The conclusions will also be reported

    Analysis of Environmental Chemical Mixtures and Non-Hodgkin Lymphoma Risk in the NCI-SEER NHL Study

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    Background: There are several suspected environmental risk factors for non-Hodgkin lymphoma (NHL). The associations between NHL and environmental chemical exposures have typically been evaluated for individual chemicals (i.e., one-by-one). Objectives: We determined the association between a mixture of 27 correlated chemicals measured in house dust and NHL risk. Methods: We conducted a population-based case–control study of NHL in four National Cancer Institute–Surveillance, Epidemiology, and End Results centers—Detroit, Michigan; Iowa; Los Angeles County, California; and Seattle, Washington—from 1998 to 2000. We used weighted quantile sum (WQS) regression to model the association of a mixture of chemicals and risk of NHL. The WQS index was a sum of weighted quartiles for 5 polychlorinated biphenyls (PCBs), 7 polycyclic aromatic hydrocarbons (PAHs), and 15 pesticides. We estimated chemical mixture weights and effects for study sites combined and for each site individually, and also for histologic subtypes of NHL. Results: The WQS index was statistically significantly associated with NHL overall [odds ratio (OR) = 1.30; 95% CI: 1.08, 1.56; p = 0.006; for one quartile increase] and in the study sites of Detroit (OR = 1.71; 95% CI: 1.02, 2.92; p = 0.045), Los Angeles (OR = 1.44; 95% CI: 1.00, 2.08; p = 0.049), and Iowa (OR = 1.76; 95% CI: 1.23, 2.53; p = 0.002). The index was marginally statistically significant in Seattle (OR = 1.39; 95% CI: 0.97, 1.99; p = 0.071). The most highly weighted chemicals for predicting risk overall were PCB congener 180 and propoxur. Highly weighted chemicals varied by study site; PCBs were more highly weighted in Detroit, and pesticides were more highly weighted in Iowa. Conclusions: An index of chemical mixtures was significantly associated with NHL. Our results show the importance of evaluating chemical mixtures when studying cancer risk

    HLA class I and II diversity contributes to the etiologic heterogeneity of non-Hodgkin lymphoma subtypes

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    A growing number of loci within the human leukocyte antigen (HLA) region have been implicated in non-Hodgkin lymphoma (NHL) etiology. Here, we test a complementary hypothesis of "heterozygote advantage" regarding the role of HLA and NHL, whereby HLA diversity is beneficial and homozygous HLA loci are associated with increased disease risk. HLA alleles at class I and II loci were imputed from genome-wide association studies (GWAS) using SNP2HLA for 3,617 diffuse large B-cell lymphomas (DLBCL), 2,686 follicular lymphomas (FL), 2,878 chronic lymphocytic leukemia/small lymphocytic lymphomas (CLL/SLL), 741 marginal zone lymphomas (MZL), and 8,753 controls of European descent. Both DLBCL and MZL risk were elevated with homozygosity at class I HLA-B and -C loci (OR DLBCL = 1.31, 95% CI = 1.06–1.60; OR MZL = 1.45, 95% CI = 1.12–1.89) and class II HLA-DRB1 locus (OR DLBCL = 2.10, 95% CI = 1.24–3.55; OR MZL = 2.10, 95% CI = 0.99–4.45). Increased FL risk was observed with the overall increase in number of homozygous HLA class II loci (P trend < 0.0001, FDR = 0.0005). These results support a role for HLA zygosity in NHL etiology and suggests that distinct immune pathways may underly the etiology of the different NHL subtypes. Significance: HLA gene diversity reduces risk for non-Hodgkin lymphoma

    Ovarian cancer risk factors by tumor aggressiveness: an analysis from the Ovarian Cancer Cohort Consortium

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    Ovarian cancer risk factors differ by histotype; however, within subtype there is substantial variability in outcomes. We hypothesized that risk factor profiles may influence tumor aggressiveness, defined by time between diagnosis and death, independent of histology. Among 1.3 million women from 21 prospective cohorts, 4,584 invasive epithelial ovarian cancers were identified and classified as highly aggressive (death in <1 year, n=864), very aggressive (death in 1-<3 years, n=1,390), moderately aggressive (death in 3-<5 years, n=639), and less aggressive (lived 5+ years, n=1,691). Using competing risks Cox proportional hazards regression, we assessed heterogeneity of associations by tumor aggressiveness for all cases and among serous and endometrioid/clear cell tumors. Associations between parity (phet =0.01), family history of ovarian cancer (phet =0.02), body mass index (BMI; phet ≤0.04) and smoking (phet <0.01) and ovarian cancer risk differed by aggressiveness. A first/single pregnancy, relative to nulliparity, was inversely associated with highly aggressive disease (HR: 0.72; 95% CI [0.58-0.88]), no association was observed for subsequent pregnancies (per pregnancy, 0.97 [0.92-1.02]). In contrast, first and subsequent pregnancies were similarly associated with less aggressive disease (0.87 for both). Family history of ovarian cancer was only associated with risk of less aggressive disease (1.94 [1.47-2.55]). High BMI (≥35 vs. 20-<25 kg/m2 , 1.93 [1.46-2.56] and current smoking (vs. never, 1.30 [1.07-1.57]) were associated with increased risk of highly aggressive disease. Results were similar within histotypes. Ovarian cancer risk factors may be directly associated with subtypes defined by tumor aggressiveness, rather than through differential effects on histology. Studies to assess biological pathways are warranted

    Correlates of Circulating 25-Hydroxyvitamin D: Cohort Consortium Vitamin D Pooling Project of Rarer Cancers

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    Low vitamin D status is common globally and is associated with multiple disease outcomes. Understanding the correlates of vitamin D status will help guide clinical practice, research, and interpretation of studies. Correlates of circulating 25-hydroxyvitamin D (25(OH)D) concentrations measured in a single laboratory were examined in 4,723 cancer-free men and women from 10 cohorts participating in the Cohort Consortium Vitamin D Pooling Project of Rarer Cancers, which covers a worldwide geographic area. Demographic and lifestyle characteristics were examined in relation to 25(OH)D using stepwise linear regression and polytomous logistic regression. The prevalence of 25(OH)D concentrations less than 25 nmol/L ranged from 3% to 36% across cohorts, and the prevalence of 25(OH)D concentrations less than 50 nmol/L ranged from 29% to 82%. Seasonal differences in circulating 25(OH)D were most marked among whites from northern latitudes. Statistically significant positive correlates of 25(OH)D included male sex, summer blood draw, vigorous physical activity, vitamin D intake, fish intake, multivitamin use, and calcium supplement use. Significant inverse correlates were body mass index, winter and spring blood draw, history of diabetes, sedentary behavior, smoking, and black race/ethnicity. Correlates varied somewhat within season, race/ethnicity, and sex. These findings help identify persons at risk for low vitamin D status for both clinical and research purposes
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