Blasting Quarry Operations: Land Use Compatibility Issues and Potential Property Value Impacts
Bibliographic record
Abstract
Aggregate resources are essential for road and building construction. In 2019, the US domestic production reached 1.53 billion tons of crushed stone valued at $18.7 billion produced by an estimated 1,430 companies operating 3,440 quarries, according to the U.S. Geological Survey (USGS) Mineral Commodity Summaries. But, it is also recognized that a quarry blasting below the water table is one of the most noxious, toxic and destructive uses of land, with no reasonable prospect of post-extraction-rehabilitation. If permitted and established in the wrong geographic location, a blasting quarry operation can result in significant deleterious impacts on the environment and local inhabitants and can disrupt short and long-term land use planning objectives. Because a quarry can remain operational for 100+ years, impacting five or more generations; quarries have the potential to cause permanent environmental degradation, destabilize communities, damage, sterilize or diminish the use and enjoyment of residential and non-residential properties, and reduce property values. Blasting is the preferred method of extracting rock in a quarry operation, the consequences of which can lead to environmental and property damage, and to injury or death of human and non-human life. In North America, licensing and operational oversight of a pit or quarry are primarily controlled by the individual states, territories and provinces, and address matters of compliance, while issues related to land use planning and zoning are entirely within the jurisdiction of the local municipalities, counties or regions. Accordingly, this research paper seeks to inform land use planners of the importance of protecting the environment and its inhabitants from the adverse effects, including the diminution in property values, associated with aggregate extraction operations generally and blasting quarries specifically, through the use of permanent onsite setbacks and offsite separation distances to avoid land use incompatibility and sensitive land uses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".