Atmospheric Lead Emissions from Coal-Fired Power Plants with Different Boilers and APCDs in Guizhou, Southwest China
Bibliographic record
Abstract
Lead (Pb) emissions into the atmosphere from anthropogenic sources have attracted considerable attention due to lead’s high toxicity and associated human health and environmental impacts. Pb emission inventories need to be updated considering the development of modern industry as well as the transformation and upgrading of industrial equipment in recent years. Coal-fired power plants (CFPPs) have been an important source of atmospheric Pb emission in China since the late 1990s, while tremendous advantages have been achieved in the air-pollution control devices (APCDs) in the most recent two decades. In this study, Pb emissions from eight CFPPs, two of which have circulating fluidized bed boilers (CFB) and the others have pulverized coal fired boilers (PC), in Guizhou province, Southwest China were investigated. Solid samples including feed fuel (coal, gangue, and coal slime), limestone, bottom ash, fly ash, and gypsum, as well as stack flue gas samples were simultaneously collected for determining the internal partitioning behavior and the atmospheric emissions of Pb from these CFPPs. Pb concentrations of feed coal, limestone, bottom ash, fly ash, gypsum, and stack flue gas were in the range of 10.17–30.94, 0.36–3.08, 7.75–27.10, 33.56–73.16, 0.34–2.18 mg·kg–1, and 0.33–1.58 μg·Nm−3, respectively. The mass balance (output/input) ratio of Pb was in the range of 83.73–124.95%, with input dominated by the feed coal (95.89–99.96%) and output by fly ash (73.17–97.54%), followed by bottom ash (2.16–26.76%) and atmospheric emissions (0.01–0.08%). More Pb ended up in PC fly ash (88.89–97.54%) than CFB fly ash (73.17–81.19%), but an opposite trend was found in the bottom ash for different boilers. Pb emission factors (EMFs) could not be differentiated significantly between PC and CFB boilers, which were in the range of 2.32–10.67 mg·t–1 fuel, 1.28–6.51 μg·(kW·h)−1, or 0.12–0.51 g·TJ–1. Atmospheric Pb emissions from Guizhou’s CFPP were estimated to be 430 ± 163 kg·y–1 in 2017, much lower than previously reported values.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".