Elemental Hg (Hg0), reactive gaseous Hg (RGM) and fine particulate Hg (Hgp) were measured intermittently at three sites in the southeastern U.S. from June 2001 through November 2004. Simultaneous measurements of SO2 and NOy were used to identify plumes from coal fired power plants (CFPPs). Emission signatures and back trajectories were used to identity specific CFPPs, and to compare observed (i.e., at the site) versus expected (i.e., at the stack) Hg speciation. Results for 41 precipitation-free plume events show that observed RGM:SO2 is substantially lower (by a factor of 2-4) than expected RGM:SO2. Hgp represented 2%, or less, of total-Hg in CFPP plumes, in general agreement with emission estimates. Results for 21 events, where both RGM and Hg0 could be estimated, show that total-Hg (i.e., RGM + Hg0) was essentially conserved from the point of emission to the site, and that Hg0 was the dominant form (average 84%). Emission estimates, based on coal analyses and the EPRI-ICR Hg speciation model, indicate that Hg0 should represent about 42% of Hg in the observed plumes. Possible explanations for these differences include, but are not limited to, in-plume reduction of RGM to Hg0, measurement error, errors in emission estimates, and depositional losses. Further work is needed to confirm these results and to determine if they apply to CFPPs in general, or the limited set of observed CFPPs.
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Despite an increasing number of studies examining the effect of Single-Photon Emission Computed Tomography/ Computed Tomography (SPECT/CT) on improvement of diagnosis of aseptic loosening, there is still a great deal of uncertainty regarding its applicability in diagnostic algorithm. Therefore, in this meta-analysis, we aimed to investigate the diagnostic performance of SPECT/CT for identification of aseptic loosening in patients with persistent pain following the total knee arthroplasty (TKA) and total hip arthroplasty (THA). Electronic databases including Medline, Scopus, Web of Science, Cochrane library, and Embase were systematically searched for identifying relevant published studies from their inception to April 2023.
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January 2025
Bhaskaracharya College of Applied Sciences, University of Delhi, New Delhi, Delhi, 110078, India.
This study investigates the spatio-temporal distribution of formaldehyde (HCHO) over the mainland Southeast Asian region (including Northeast India) from 2019 to 2022 using TROPOMI satellite data. HCHO is a key atmospheric trace gas which is influenced by both natural processes and anthropogenic activities. We analyze HCHO levels in relation to atmospheric species including carbon monoxide (CO), nitrogen dioxide (NO), and environmental factors such as land surface temperature (LST), precipitation (PPT), fire radiative power (FRP), and enhanced vegetation index (EVI).
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Tianjin Key Laboratory of Environmental Technology for Complex Trans-Media Pollution, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
Wastewater treatment plants (WWTPs) are significant sources of microplastic (MP) emissions. In order to quantify the potential MP emission from WWTPs, a database of more than 10,000 WWTPs in China with an estimated MP emission rate was built. The MP riverine retention after emission was also estimated based on Stokes' law for both fragments and fibers.
View Article and Find Full Text PDFEnviron Res
January 2025
China Academy of Safety Science and Technology, Beijing 100012, China. Electronic address:
Spontaneous coal fires are a significant source of greenhouse gas emissions, contributing to global warming. However, the lack of reliable estimation methods and research has obscured the full environmental impact of these emissions. This paper presents a novel quantification method for fugitive carbon emissions from spontaneous coal combustion.
View Article and Find Full Text PDFJ Hazard Mater
January 2025
Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, PR China; Institute of Eco-Chongming (IEC), 20 Cuiniao Road, Chenjia Town, Chongming District, Shanghai 202162, PR China. Electronic address:
As one of the significant air pollutants, nitrogen oxides (NO = NO + NO) not only pose a great threat to human health, but also contribute to the formation of secondary pollutants such as ozone and nitrate particles. Due to substantial uncertainties in bottom-up emission inventories, simulated concentrations of air pollutants using GEOS-Chem model often largely biased from those of ground-level observations. To address this issue, we developed a new deep learning model to simulate the inverse process of the GEOS-Chem model.
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