Key Takeaways & Executive Findings
- •• • Interannual coal dust pollution in the Baorixile mining area (2001-2024) followed a three-stage lifecycle pattern: fluctuating increase (2001-2010), significant decrease (2010-2016), and stabilization (2016-2024), with the average pollution degree peaking at 0.41 in 2010 and stabilizing at 0.18-0.22 thereafter, indicating effective mitigation after peak production. • • Seasonal analysis (2019-2023) revealed a unimodal intra-annual pattern: summer pollution was most severe, followed by autumn, spring, and winter, providing a temporal basis for season-specific dust control measures. • • Multi-year dust impact frequency (DIF) analysis (2001-2024) showed that the maximum impact range (DIF≥1) first expanded then contracted significantly, while the perennial impact area (DIF=4) migrated from the southeast to the central-western open-pit, demonstrating a shift in dust disturbance gravity and successful containment. • • Intra-annual DIF (2019-2024) exhibited a spatial gradient decreasing from the core operation area to the periphery, with high-frequency zones (DIF≥9) stably concentrated in the open-pit; the affected area decreased from 88.14 km² in 2019 to 72.84 km² in 2024, a 17.4% reduction, highlighting the efficacy of ongoing dust suppression.
Abstract
Coal dust from open-pit mining severely impacts the mining area and surrounding environment, exhibiting significant dynamic changes. However, quantitative assessments of the pollution extent and multi-timescale evolution remain insufficient. Based on the Google Earth Engine platform and Landsat TM/ETM+/OLI/OLI-2 and Sentinel-2 MSI imagery from 2001 to 2024, we retrieved the enhanced coal dust index (ECDI) and coal dust pollution levels. Combined with the mine lifecycle stages, we revealed the temporal and spatial variations of coal dust in the Baorixile mining area. Annual and monthly remote sensing retrievals were stacked to construct multi-year and intra-annual dust impact frequency (DIF) indicators, precisely quantifying the spatial extent and frequency of coal dust pollution. Results show that from 2001 to 2024, the interannual coal dust pollution experienced three stages: fluctuating increase, significant decrease, and stabilization. The average pollution degree peaked at 0.41 in 2010 and remained between 0.18 and 0.22 from 2016 to 2024. The spatial pattern improved, converging from widespread diffusion to the open-pit and bare coal accumulation areas. From 2019 to 2023, intra-annual pollution increased then decreased, with summer most severe, followed by autumn, spring, and winter. Based on annual retrievals, 6 periods of multi-year DIF (2001-2024) were generated at 4-year intervals. The maximum impact range (DIF≥1) first expanded then contracted significantly; the perennial impact area (DIF=4) shifted from the southeast to the central-western open-pit, indicating a notable migration of dust disturbance gravity and effective control. Based on monthly retrievals, 6 periods of intra-annual DIF (2019-2024) were generated at 12-month intervals. The intra-annual DIF showed a gradient decreasing from the core operation area to the periphery. High-frequency zones (DIF≥9) were stably concentrated in the open-pit. The affected area fluctuated downward from 88.14 km² in 2019 to 72.84 km² in 2024. This study provides theoretical and data support for scientifically understanding and monitoring the ecological status of mining areas and formulating dust suppression measures.
1. Introduction
Coal mining in resource-based regions drives economic development but generates severe dust pollution, leading to soil degradation, vegetation loss, water contamination, and health risks. Conventional monitoring methods—fixed stations and mobile sensors—offer high accuracy but are limited in spatial coverage and temporal resolution, failing to capture the dynamic, large-scale pollution patterns typical of open-pit mines. Numerical simulations, while useful for forecasting, suffer from uncertainties in input parameters and environmental variability, limiting their precision in real-world applications.
Remote sensing, leveraging satellite platforms, provides a macroscopic and repeatable approach to monitor coal dust pollution. However, existing indices often lack specificity or are applied over short timeframes, hindering the assessment of long-term trends and frequency of dust impacts. This study addresses these gaps by employing the enhanced coal dust index (ECDI) on a 24-year Landsat and Sentinel-2 time series within the Google Earth Engine, enabling systematic quantification of dust pollution dynamics across annual and monthly scales. The introduction of dust impact frequency (DIF) metrics further allows for the first time a quantitative evaluation of pollution persistence and spatial shifts, offering a robust framework for ecological monitoring and targeted mitigation strategies in large-scale coal bases.
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GAO Sihua, HUO Jiangrun, LI Jing, ZHANG Jinpeng, FU Xiao, WANG Yujue, WANG Kewen (2026). Spatiotemporal Variation Characteristics of Coal Dust Pollution in the Baorixile Mining Area. Chinese Journal of Environmental Engineering. https://doi.org/10.12030/j.cjee.202502081
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Frequently Asked Questions
What is the enhanced coal dust index (ECDI) and how does it differ from previous indices in terms of accuracy and applicability?
The ECDI is a spectral index designed to enhance the contrast between coal dust and background surfaces, improving detection accuracy. While the paper does not provide explicit accuracy metrics, the index was applied successfully over a 24-year period using multi-sensor data, indicating robustness. Compared to earlier indices like the normalized difference coal index, ECDI likely incorporates additional spectral bands to better discriminate coal dust from other dark surfaces, but further validation against ground truth is recommended.
How do the seasonal variations in coal dust pollution (summer > autumn > spring > winter) correlate with meteorological conditions and mining activity?
The observed seasonal pattern is likely driven by a combination of factors: higher temperatures and lower precipitation in summer may increase dust generation and suspension, while winter snow cover suppresses dust. Additionally, mining activity may intensify during summer months. The paper does not provide a detailed correlation analysis, but the findings suggest that dust control measures should be prioritized in summer, possibly through increased watering or chemical suppressants.
What are the limitations of using Landsat and Sentinel-2 data for coal dust monitoring, particularly regarding cloud cover and temporal resolution?
Optical remote sensing is hindered by cloud cover, which can reduce the number of usable images, especially in regions with frequent cloudiness. The study likely used compositing techniques to mitigate this, but the temporal resolution may still be insufficient to capture short-term dust events. The paper does not specify the number of images used per year, but the use of both Landsat and Sentinel-2 increases revisit frequency. For operational monitoring, integrating SAR data or higher-temporal-resolution sensors could be beneficial.
How does the dust impact frequency (DIF) metric account for the severity of pollution, and can it be used to set regulatory thresholds?
DIF is defined as the number of times a pixel is classified as polluted over a given period (e.g., 4 years for multi-year DIF, 12 months for intra-annual DIF). It does not directly incorporate severity (e.g., concentration levels), but rather frequency of occurrence. This metric is useful for identifying persistent pollution zones, which are critical for prioritizing remediation. Regulatory thresholds could be set based on DIF values, e.g., areas with DIF≥9 (high frequency) may require immediate intervention, while DIF=4 (perennial) indicates chronic pollution. However, linking DIF to health or ecological risk would require additional data.
What are the implications of the observed reduction in affected area from 88.14 km² in 2019 to 72.84 km² in 2024 for the effectiveness of current dust suppression measures?
The 17.4% reduction in affected area over five years suggests that existing dust suppression measures, such as watering, chemical stabilizers, and vegetation restoration, are effective. However, the persistence of high-frequency zones (DIF≥9) in the open-pit indicates that source control remains challenging. Future efforts should focus on reducing emissions at the source, possibly through improved mining practices or enhanced dust collection systems. The study provides a quantitative baseline for evaluating the success of such measures.
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