*3.3. Measured Data*

In the end of the data-collection phase, 500 event structures were recorded. Each event instance has 15 s worth of data saved into files: 15 JPG files containing the captured images and one text file containing the rest of the measured data. The text file is structured so every second of the event is one line (separated by a newline character "\n"), and the measured quantities are separated by commas. Table 3 shows an example of the numeric data measured during one event.

**Figure 4.** Flowchart of decision process and data flow within DAS software.

The first column contains the time stamps from each measurement point in the event. Each component is separated by an underscore, following the "hh\_mm\_ss\_YYYY\_MM\_DD" format. The last component is a Boolean value, indicating whether daylight savings time is in effect. This is in local time and is used to determine the solar position angles.

Next are temperature measurements taken once per event, if, as with this example, there is more than one value in one event, it is because events were detected close to one another and some of the time stamps intersect. The negative values were used to represent "no data", and those were replaced by linear interpolations for the data-modeling phase. The last three values are the measured voltage, current and power, respectively. One such file was generated per detected event. As for the captured images, Figure 5 shows two examples of raw images, one from the beginning of the event and the second from the end.

**Table 3.** Example of numeric data pertaining to one event structure.

(**a**) (**b**)

**Figure 5.** Raw image examples from the beginning of an event (**a**) and from the end (**b**).


**1. Introduction**

The volumes of production/consumption of rare and rare-earth metals, which are critical for modern industries, are steadily increasing [1–4]. In this group of metals—scandium, yttrium, lanthanum, and lanthanides—scandium is the most scarce and commercially attractive one. The increased interest in scandium is associated with its application in various industries [5–7]. Small amounts of scandium are found in ores of aluminum, cobalt, iron, molybdenum, nickel, phosphate, titanium, tungsten, uranium, and others [8–16].

At the moment, phosphogypsum—waste from the processing of apatite concentrates [17,18]—and red mud (bauxite residue) are considered to be the most promising sources of scandium [19–24]. Phosphogypsum is also considered to be the most promising source of other rare earth metals [6], as it may contain up to 1% of rare earth elements in total [25]. More than 250 million tons of phosphogypsum has been accumulated in Russia [26] with an annual increase by over 14 million tons. However, despite the large number of works devoted to the processing of phosphogypsum, there is still no commercially viable technology for its processing [27], which is explained by isomorphic co-crystallization of REE with gypsum, and therefore the need for its complete release [28].

Bauxite residue generated in the recovery and processing of bauxites is a source of environmental pollution [29,30] on the one hand and a promising object for obtaining valuable elements [31] on the other hand. Bauxite residue contains a high amount of scandium (70–260 ppm) that is close to its primary resources [32]. Large amounts of this waste form what may be called man-made deposits, which can be recycled into building materials, pigments, coagulants for wastewater treatment, and which can be used to re-extract alumina, extract iron concentrates, titanium, rare and rare earth metals [33–35]. In the industrial production of alumina, almost all Sc is concentrated in red mud. According to available estimates, the global reserves of scandium in the industrial waste range from 1 to 3 million tons, with 70–80% of it being contained in bauxite processing waste [36]. The full processing of the bauxite residue currently generated makes it possible to extract 6600–20,400 t of scandium per year. Therefore, a large number of studies have been dedicated to the recovery of rare-earth metals from various types of bauxite residue [37] obtained by processing various bauxites in the Bayer method and its variations. However, the low content of scandium in the red mud, the high content of alkali and alkaline earth metals, and the simultaneous recovery of iron together with REE [38] or low extraction efficiency [39,40] render the existing methods for extracting scandium from this type of industrial waste non-viable.

It should be noted that most studies of the separation of REE from alumina products have focused on the processing of red mud. In this article, we made an attempt to study the possibility of obtaining the REE concentrate from electrostatic precipitator (ESP) dust, which is an intermediate product of kiln sintering in alumina production. The dust is generated in a rotary kiln (Figure 1), where low-quality bauxite (the mass ratio of Al2O3 to SiO2 (silicon modulus) is less than 7) is sintered with soda ash in order to convert the alumina-containing mineral into a water-soluble sodium aluminate. Iron and silicon-containing minerals react similarly with soda to form ferrite and sodium silicate, respectively. The technological process, especially at the drying and decarbonization stages, generates a large number of fine particles less than 100 μm (25–40% of the charge), which are carried away with the exhaust gases. To clean the exhaust gases of kilns from dust particles, a three-stage capture system is used. The first stage is the dust chamber where most coarse dust particles precipitate; the second stage is cyclones, where medium dust particles are removed from the exhaust gases through vortex separation; and the final stage is electrostatic precipitator. The last stage captures the finest particle fraction (less than 20 μm) using the force of an induced electrostatic charge.

**Figure 1.** Flow chart of the sintering process on the RUSAL-Kamensk-Uralsky alumina refinery.

It is impossible to remove all dust from the technological process since that would upset the heat balance of the furnace and would greatly complicate the movement of the charge in the drying zone. On the other hand, the ESP dust acts mostly as a dead weight, since a number of dust circulations through the kiln are larger than through all other units of the gas treatment system. Electrostatic precipitators capture only the smallest particles, which often pass very quickly through the hot zones of the furnace, and the sintering process fails to complete. Ultimately, they acquire the charge of the electrostatic precipitator and are released into the atmosphere. The physicochemical properties of sintering dust and the possibility of their leaching together with bauxite had already been investigated in our previous work [41]. It was shown that ESP dust can be highly reactive and can be removed from the process with further leaching to extract useful components. Also, the high recovery rate of ESP dust means significant losses of secondary heat. The proportion of ESP dust in the total mass of dust is up to 15%, which means that alumina refineries in Russia produce more than 30 thousand tons of ESP dust per year. At the same time, ESP dust contains about 50 ppm of scandium [42]. Therefore, more than 1.5 t of scandium and even more of other rare earth metals can be obtained annually from this intermediate product.

In this work we studied the possibility of leaching ESP dust with water and mother liquor of the Bayer process in order to extract rare-earth elements into valuable components such as alumina, caustic alkali, and soda, and, at the same time, concentrate them in the red mud resulting from leaching.

#### **2. Materials and Methods**

#### *2.1. Solid Phase Characterization*

The phase and quantitative composition of the ESP dust from sintering kilns of the Kamensk-Uralsky alumina refinery and leaching products were determined by X-ray diffraction (XRD) on a Rigaku D/MAX-2200 diffractometer (Rikagu Corp., Tokyo, Japan) using the PDF-2 database (International Center for Diffraction Data) and by X-ray fluorescence (XRF) using an Axios MAX X-ray fluorescence spectrometer (Malvern Panalytical Ltd., Almelo, The Netherlands). The content of REE micro impurities in the feedstock and leachate was determined using inductively coupled plasma mass spectrometry (ICP-MS) on a PerkinElmer NexION 300S instrument (PerkinElmer Inc., Waltham, MA, USA).

Electron probe micro-analysis (EPMA) was performed using a Cameca SX 100 microanalyzer (CAMECA Instruments, Inc., Madison, WI, USA) equipped with an energy-dispersive X-ray spectroscopy analysis (EDS) module Bruker XFlash 6 (Bruker Nano GmbH, Berlin, Germany).


**3. Results**

Female BC incidence rates increased with age until a peak in the 70–74 year age group (Figure 1). Between 2010 and 2017, less than half (46.1%) of all new primary BC cases were diagnosed in women aged 50–74, the age range recommended by current screening guidelines. This percentage increased by almost 9 percentage points to 54.6% when women

in their forties are included. The number of BC cases diagnosed in women aged 40–49 was equivalent to 18.5% of the total number of BC cases in screened women aged 50–74. The incidence rate ratio between cases diagnosed in the 40s and those diagnosed in their 50s was 0.63.

**Figure 1.** Age–specific female breast cancer incidence rate, by five–year age group, Canada excluding Quebec, 2010 to 2017 period. Note: Quebec is excluded because cases diagnosed in Quebec from 2011 onward had not been submitted to the Canadian Cancer Registry. Solid lines display current ages included in screening; dashed line indicates the age threshold where screening is being explored. Source: Canadian Cancer Registry (1992 to 2018) at Statistics Canada [42].

The proportion of women diagnosed with stage I BC was observed to be greater among those aged 50–74 at diagnosis—for whom screening is currently recommended— than among those diagnosed outside of this age range (Figure 2). Canadian women aged 50–74 had a proportionally higher incidence of stage I BC, and lower relative proportions of stage II and III BC, compared with younger and older women who fall outside the CTFPHC recommended screening age.

**Figure 2.** Stage–specific distribution of female breast cancer cases by age group at diagnosis, Canada excluding Quebec, 2010 to 2017 period. Note: Quebec is excluded because cases diagnosed in Quebec from 2011 onward had not been submitted to the Canadian Cancer Registry. The ages between the dashed lines represent those age groups for which mammogram screening is currently recommended. Source: Canadian Cancer Registry (1992 to 2018) at Statistics Canada [42].

The distribution of BC stage at diagnosis was significantly different between women aged 50–59 and their 40–49 year counterparts not targeted by screening programs (Figure 3, Table 2). Except for stage IV, Canadian women aged 40–49 had BC diagnosed at significantly later stages than those aged 50–59 who had higher relative proportions of stage I BC (45.3% vs. 35.7%; *p* < 0.001), and lower proportions of stage II (36.7% vs. 42.6%, *p* < 0.001), and III (13.1% vs. 17.3%, *p* < 0.001) BC. The proportion of stage IV at diagnosis in women aged 40–49 was significantly lower than in women aged 50–59 years old (4.4% vs. 4.8%, *p* = 0.005).

**Figure 3.** Stage–specific distribution of female breast cancer cases, ages 40 to 49 years versus ages 50 to 59 years, Canada excluding Quebec, 2010 to 2017. Note: Quebec is excluded because cases diagnosed in Quebec from 2011 onward had not been submitted to the Canadian Cancer Registry. Vertical error bars indicate 95% confidence intervals. Source: Canadian Cancer Registry (1992 to 2018) at Statistics Canada [42].

**Table 2.** Number and proportion of women diagnosed with breast cancer by stage at diagnosis, ages 40 to 49 years versus 50 to 59 years, Canada excluding Quebec, 2010 to 2017 period.

NA = not applicable, CI = confidence interval. Note: Quebec is excluded because cases diagnosed in Quebec from 2011 onward had not been submitted to the Canadian Cancer Registry. Counts have been randomly rounded to a multiple of five in accordance with Statistics Canada's disclosure-avoidance guidelines. Source: Canadian Cancer Registry (1992 to 2018) at Statistics Canada [42].