Abstract
In open-pit mining, there is a significant source of particulate matter (PM) in theatmosphere due to continuous earthmoving, mineral size reduction, treatment,
and storage operations. This high PM concentration is associated with adverse
health effects, raising public health concerns regarding fugitive emissions from
mining activities. However, due to the large scale of these operations,
conventional control of these emissions proves to be challenging and expensive,
motivating the mining industry to seek more efficient and cost-effective
technologies. This thesis introduces innovative tools for addressing air quality
monitoring in mining environments and their surrounding areas. These tools aim
to enable a detailed study of pollutant distribution, thus facilitating decision
support in situations of high pollutant concentration and continuous air quality
monitoring in these regions.
The experimental work for this doctoral thesis was conducted entirely within the
premises of the Cerro Colorado open-pit mine, located in Riotinto, Huelva, one of
the largest and most significant open-pit metal mines in Europe. It also
encompassed an analysis of the mine's contribution to the nearby communities.
The study begins with an extensive PM10 sampling campaign carried out in three
towns within the Riotinto district. The results showed that average PM10
concentrations exceeded annual and daily limits in the population closest to the
mine during the spring and summer. Furthermore, a significant enrichment of
potentially toxic elements (referred to as EPT or PTE in English) was observed.
The most significant finding was the substantial contribution of the mine to the
enrichment of these contaminants, especially in the nearby communities. This
finding motivated the development of tools for PM monitoring inside the mine.
A novel methodology is proposed for the space-time monitoring of PM
concentrations in open-pit mines using low-cost mobile sensors (referred to as
Low-cost Sensors, or LCS), costing less than 300 €. These sensors were placed
at various locations, ranging from areas with zero activity to intensely active
mining zones. Detailed calibration of the mobile LCS was conducted to meet
European standards. The results revealed PM concentrations, maximum and
minimum levels, seasonal variations, and the primary sources of PM within the
VI
mine. The integration of these data with meteorological information allowed for
the identification of pathways for fugitive emissions toward nearby populations,
providing significant insights into addressing this issue in the mining industry.
The study demonstrated the applicability of LCS for high-resolution PM
monitoring in mining, supporting environmental managers in cost-effective
decision-making against fugitive emissions. Together, these advancements
represent a significant step towards a more sustainable and environmentally
friendly mining industry.
While a substantial portion of the study was conducted using commercial LCS,
this thesis also proposed a custom wireless sensor network (WSN) design
employing LoRaWAN technology. This solution meets scalability, low power
consumption, autonomy, and deployment simplicity requirements, with a compact
and customized hardware design. The system combines WSN with IoT and cloud
computing, allowing real-time data visualization and providing the mining industry
with a tool to make decisions aimed at minimizing PM generation when specific
threshold alerts are triggered.
| Date of Award | 2024 |
|---|---|
| Original language | English |
| Awarding Institution |
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