Friday, 26 August 2022

Monkeypox vs Covid – The First 100 Days

The Covid-19 pandemic is apparently over (but maybe not, time will tell), but now comes Monkeypox. So, an obvious question that comes to mind is, how does the beginning of the global Monkeypox outbreak compare to the start of the global Covid outbreak? To that end, this essay has mined some data from Our World in Data to make these comparisons, along with making some reasonable assumptions to put them into perspective.

Straight-up Comparison

The graph below is a straight-up comparison of the raw data, for the first 100 days, of the course of the two outbreaks. Looking at it this way, there is little similarity between the two; Covid-19 was a much more extreme outbreak than Monkeypox has been, at least so far.

Adjustment for Uncertainty in Start Dates

One problem with this comparison, is that it is difficult to say just when the two outbreaks began. The first day of the published data for the Covid-19 outbreak has 557 cases listed, which is obviously wrong. On the other hand, the published data for the Monkeypox outbreak begins with only 1 case for the first two days, then jumps to 11 by the third day. (The raw data is shown at the end of the blog).

So, the data has been adjusted, imputing some new adjusted data, by back-extrapolating the first few days, via the use of a smooth power law function that fits the data rather well, after this early “scanty-data” period. The graphs below show how this was done (i.e. used the equations to calculate the earlier predicted points).

With these adjusted start dates, the new Covid vs Monkeypox graph is shown below. This closes up the comparison between the Covid and Monkeypox outbreaks somewhat, though the Covid numbers are still much higher than the Monkeypox numbers.

Adjustment for At-Risk Populations

The most recent evidence shows that the two pandemics have effected very different populations. Covid-19 was quite widespread, hitting all age groups and genders, though Covid had a tendency for severe outcomes (hospitalizations and deaths) to increase with age and it was somewhat more severe for males than females. But, in terms of cases, the entire population of a given country tended to be hit fairly equally.

On the other hand, Monkeypox was almost entirely confined to a small section of the population, which has described as “men who have sex with men” (MSM). So, a more appropriate comparison of the two outbreaks might be made by simulating Covid-19 data, as it would apply to that smaller part of the population.

To do this, a few assumptions have to be made:

MSM are males.
MSM make up about 3 percent of the male population, or about 1.5% of the population in general.
MSM that are at risk of Monkeypox are mostly in the 20 to 59 age groups (presumably, the most sexually active group).

To adjust Covid-19 cases to simulate this sub-group, the numbers for the overall population were multiplied by 0.015, which produces the graph shown below.

This graph shows that once the differences in the at-risk populations are accounted for, the early stages of these outbreaks are rather similar. Making reasonable changes in the above assumptions will alter the graph to some extent, but this essential feature will remain true.

Another way to look at the situation is to simulate Monkeypox figures, as might be the case if the virus mutated into a form that spread through the air, in the manner of the corona virus that causes Covid-19. This can be done by dividing the Monkeypox data by 0.015, yielding the graph shown below.

Although this graph has the same overall form of the previous one, it does emphasize that Monkeypox could have quite a Covid-like effect, if it was to evolve in this direction. Granted, that seems unlikely, as it is not an RNA-based virus, and thus should mutate at a much smaller rate than the SARS-2 Corona virus did.

Comparison of Deaths from Covid vs Monkeypox

So far, Monkeypox has had a very low fatality rate. As of the first 100 days, only about a dozen people were recorded as dying from Monkeypox, from a case count of over 35,000. So, that’s only about one per three thousand cases. Covid, on the other, had recorded about 240,000 fatalities by day 100. That’s a huge difference.

Or is it? Again, we have to account for the difference in at-risk populations:

There were about 3.25 million Covid cases by Day 100.
However, the MSM sub-group would only account for about 1.5% of these, or a bit under 41,000 cases.
But in this age range (20-59) the case fatality rate was very low, at about 1.2 per thousand in many industrialized counties, the set that has been hit hardest by Monkeypox.
So, that would imply about 49 fatalities in this particular sub-group of the population.

That’s about 4 times more fatalities than were seen in the Monkeypox group, implying that Covid-19 is probably more severe in its effects than Monkeypox, or at least it was in the early stages of the pandemic.

Nonetheless, it also implies that if Monkeypox were to become widespread in the overall population, the effects would be quite severe. Added to that, is the fact that Monkeypox has historically been much more severe in children than in other age groups. So, a Monkeypox pandemic that included large numbers of children could be very tragic, indeed.

So, in summary, a widespread Monkeypox pandemic would be a bad thing, something that we definitely would want to avoid.

Source Data – From Our World in Data

Original Data			Start-Date Adjusted
Day	Covid-19	Monkeypox	Day	Covid-19	Monkeypox
1	557	1	1	1	1
2	657	1	2	4	2
3	944	11	3	14	3
4	1,437	11	4	37	5
5	2,120	11	5	82	8
6	2,929	11	6	160	13
7	5,580	12	7	284	18
8	6,169	13	8	557	26
9	8,237	13	9	657	36
10	9,927	17	10	944	41
11	12,038	17	11	1,437	60
12	16,787	20	12	2,120	105
13	19,887	41	13	2,929	121
14	23,899	60	14	5,580	121
15	27,644	105	15	6,169	194
16	30,806	121	16	8,237	230
17	34,400	121	17	9,927	274
18	37,131	194	18	12,038	362
19	40,162	230	19	16,787	414
20	42,771	274	20	19,887	431
21	44,814	362	21	23,899	451
22	45,232	414	22	27,644	574
23	60,384	431	23	30,806	639
24	66,912	451	24	34,400	723
25	69,055	574	25	37,131	848
26	71,238	639	26	40,162	942
27	73,273	723	27	42,771	950
28	75,155	848	28	44,814	1,057
29	75,655	942	29	45,232	1,172
30	76,216	950	30	60,384	1,322
31	76,846	1,057	31	66,912	1,419
32	78,608	1,172	32	69,055	1,565
33	78,990	1,322	33	71,238	1,608
34	79,558	1,419	34	73,273	1,617
35	80,412	1,565	35	75,155	1,731
36	81,384	1,608	36	75,655	1,791
37	82,728	1,617	37	76,216	2,035
38	84,152	1,731	38	76,846	2,182
39	86,023	1,791	39	78,608	2,558
40	88,402	2,035	40	78,990	2,752
41	90,382	2,182	41	79,558	2,757
42	92,994	2,558	42	80,412	2,764
43	95,316	2,752	43	81,384	3,058
44	98,027	2,757	44	82,728	3,340
45	101,957	2,764	45	84,152	3,514
46	106,088	3,058	46	86,023	4,072
47	109,942	3,340	47	88,402	4,276
48	114,265	3,514	48	90,382	4,288
49	119,051	4,072	49	92,994	4,484
50	126,527	4,276	50	95,316	4,871
51	133,283	4,288	51	98,027	5,219
52	146,477	4,484	52	101,957	5,372
53	157,365	4,871	53	106,088	6,179
54	168,598	5,219	54	109,942	6,448
55	183,165	5,372	55	114,265	6,492
56	198,339	6,179	56	119,051	6,532
57	215,899	6,448	57	126,527	7,026
58	242,986	6,492	58	133,283	7,473
59	272,516	6,532	59	146,477	7,705
60	304,943	7,026	60	157,365	8,395
61	339,156	7,473	61	168,598	9,455
62	381,711	7,705	62	183,165	9,577
63	423,596	8,395	63	198,339	9,604
64	475,075	9,455	64	215,899	10,195
65	535,890	9,577	65	242,986	11,067
66	599,820	9,604	66	272,516	11,485
67	669,402	10,195	67	304,943	12,096
68	725,918	11,067	68	339,156	12,984
69	790,929	11,485	69	381,711	13,000
70	869,371	12,096	70	423,596	13,038
71	951,084	12,984	71	475,075	13,855
72	1,033,528	13,000	72	535,890	15,049
73	1,117,697	13,038	73	599,820	15,623
74	1,177,956	13,855	74	669,402	16,263
75	1,250,135	15,049	75	725,918	16,983
76	1,324,652	15,623	76	790,929	16,987
77	1,393,480	16,263	77	869,371	17,021
78	1,475,476	16,983	78	951,084	18,307
79	1,562,248	16,987	79	1,033,528	19,842
80	1,648,773	17,021	80	1,117,697	20,995
81	1,724,228	18,307	81	1,177,956	21,836
82	1,843,259	19,842	82	1,250,135	23,056
83	1,914,995	20,995	83	1,324,652	23,141
84	1,999,444	21,836	84	1,393,480	23,273
85	2,077,235	23,056	85	1,475,476	24,490
86	2,171,659	23,141	86	1,562,248	25,932
87	2,259,490	23,273	87	1,648,773	26,585
88	2,337,722	24,490	88	1,724,228	27,708
89	2,414,435	25,932	89	1,843,259	28,875
90	2,490,358	26,585	90	1,914,995	28,989
91	2,566,573	27,708	91	1,999,444	29,129
92	2,648,525	28,875	92	2,077,235	31,116
93	2,731,129	28,989	93	2,171,659	32,549
94	2,815,167	29,129	94	2,259,490	33,700
95	2,898,660	31,116	95	2,337,722	34,388
96	2,969,529	32,549	96	2,414,435	35,797
97	3,040,471	33,700	97	2,490,358	35,940
98	3,116,272	34,388	98	2,566,573	36,060
99	3,193,642	35,797	99	2,648,525	37,534
100	3,277,493	35,940	100	2,731,129	38,853

Sources:

https://ourworldindata.org/monkeypox

https://www.cebm.net/covid-19/excess-mortality-across-countries-in-2020/

https://www.worldometers.info/coronavirus/#countries

Some earlier Covid-19 blogs:

https://dodecahedronbooks.blogspot.com/2021/03/covid-19-vaccines-positive-results-from.html

https://dodecahedronbooks.blogspot.com/2021/03/covid-19-vaccines-how-successfully-are.html

https://dodecahedronbooks.blogspot.com/2020/12/covid-19-vaccines-comparison-of.html

https://dodecahedronbooks.blogspot.com/2020/09/covid-19-continues-to-travel-around.html

https://dodecahedronbooks.blogspot.com/2020/07/has-covid-19-become-less-deadly.html

https://dodecahedronbooks.blogspot.com/2020/07/july-2020-update-covid-19-death-rates.html

https://dodecahedronbooks.blogspot.com/2020/05/covid-19-death-rates-correlate-highly.html

https://dodecahedronbooks.blogspot.com/2020/06/covid-19-impact-on-employment-no-impact.html

https://dodecahedronbooks.blogspot.com/2020/04/is-there-model-that-can-predict-when-to.html

https://dodecahedronbooks.blogspot.com/2020/03/estimating-fatality-rate-of-coronavirus.html

There are more Covid-related posts on the blog, that can be found from the labels coronavirus and Covid-19.

=====================================================

And, here’s a more pleasant travel story than anticipating the worldwide journey of a virus.

A Drive Across Newfoundland

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Newfoundland, Canada’s most easterly province, is a region that is both fascinating in its unique culture and amazing in its vistas of stark beauty. The weather is often wild, with coastal regions known for steep cliffs and crashing waves (though tranquil beaches exist too). The inland areas are primarily Precambrian shield, dominated by forests, rivers, rock formations, and abundant wildlife. The province also features some of the Earth’s most remarkable geology, notably The Tablelands, where the mantle rocks of the Earth’s interior have been exposed at the surface, permitting one to explore an almost alien landscape, an opportunity available on only a few scattered regions of the planet.

The city of St. John’s is one of Canada’s most unique urban areas, with a population that maintains many old traditions and cultural aspects of the British Isles. That’s true of the rest of the province, as well, where the people are friendly and inclined to chat amiably with visitors. Plus, they talk with amusing accents and party hard, so what’s not to like?

This account focusses on a two-week road trip in October 2007, from St. John’s in the southeast, to L’Anse aux Meadows in the far northwest, the only known Viking settlement in North America. It also features a day hike visit to The Tablelands, a remarkable and majestic geological feature. Even those who don’t normally consider themselves very interested in geology will find themselves awe-struck by these other-worldly landscapes.

A Ride on the Kettle Valley Rail Trail: A Biking Journal Kindle Edition

by Dale Olausen (Author), Helena Puumala (Editor)

The Kettle Valley Rail Trail is one of the longest and most scenic biking and hiking trails in Canada. It covers a good stretch of the south-central interior of British Columbia, about 600 kilometers of scenic countryside. British Columbia is one of the most beautiful areas of Canada, which is itself a beautiful country, ideal for those who appreciate natural splendour and achievable adventure in the great outdoors.

The trail passes through a great variety of geographical and geological regions, from mountains to valleys, along scenic lakes and rivers, to dry near-desert condition grasslands. It often features towering canyons, spanned by a combination of high trestle bridges and long tunnels, as it passes through wild, unpopulated country. At other times, it remains quite low, in populated valleys, alongside spectacular water features such as beautiful Lake Okanagan, an area that is home to hundreds of vineyards, as well as other civilized comforts.

The trail is a nice test of one’s physical fitness, as well as one’s wits and adaptability, as much of it does travel through true wilderness. The views are spectacular, the wildlife is plentiful and the people are friendly. What more could one ask for?

What follows is a journal of two summers of adventure, biking most of the trail in the late 1990s. It is about 33,000 words in length (2 to 3 hours reading), and contains numerous photographs of the trail. There are also sections containing a brief history of the trail, geology, flora and fauna, and associated information.

After reading this account, you should have a good sense of whether the trail is right for you. If you do decide to ride the trail, it will be an experience you will never forget.

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Amazon U.K.: https://www.amazon.co.uk/dp/B01GBG8JE0

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On the Road with Bronco Billy

Spring is on us now, and that brings on thoughts of ROAD TRIP. Sure, it is still a bit early, but you can still start making plans for your next road trip with help of “On the Road with Bronco Billy”. Sit back and go on a ten day trucking trip in a big rig, through western North America, from Alberta to Texas, and back again. Explore the countryside, learn some trucking lingo, and observe the shifting cultural norms across this great continent. Then, come spring, try it out for yourself.

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Amazon U.K.: http://www.amazon.co.uk/gp/product/B00X2IRHSK

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Amazon Canada: http://www.amazon.ca/gp/product/B00X2IRHSK

Friday, 29 July 2022

Globalization and the World-wide Progress of the Covid-19 Pandemic: Early-2020 to mid-2022

Covid-19 is widely considered to be related to the recent trends in globalization. Basically, viruses can hitch a ride on people, and the things that they trade, to rapidly spread around the world. This seems entirely logical, though it is always good to examine the evidence, and see how our intuitions on these matters stand up to reality.

In order to look at this, I did some simple correlations and regressions between measures of globalization and measures of Covid-19 intensity, by country, during the duration of the pandemic, from early 2020 to mid-2022.

Globalization Measures

Globalization can mean many things to many people, so how can it be quantified and measured? It turns out that there is a lot of research on the subject and a number of globalization indices have been worked out. For this purpose I will use a series of measures created by the reputable KOF Swiss Economic Institute. Here is a brief explanation of these globalization measures, as stated on their website:

“Economic globalization is composed of trade globalization and financial globalization, of which each gets a weight of 50 percent. Social globalization consists of personal contact, information flows and cultural proximity where each contributes one third. Economic, social and political globalization are aggregated to the Globalization Index using again equal weights. The overall KOF Globalization Index is calculated as the average of the de facto and the de jure Globalization Index.”

The graphs and correlation matrix below show how well these measures interact with each other, when calculated from a database of about 200 countries (each dot in the graphs corresponds to the globalization measures for a particular country). As you can see from the graphs, these measures appear to have quite a strong linear relationships (when a country is high on one variable, it is generally high on the other). The relationships between Overall Globalization, Social Globalization and Economic Globalization are especially strong, as seen by how the points tend to fall on a more or less straight lines for the relevant graphs. Political Globalization is not as strongly related, which would seem to indicate that it is measuring a somewhat different underlying phenomenon than the others.

Relationship Between Globalization Variables

In addition, they have quite high correlation coefficients. Note that a perfect positive correlation is equal to 1.00 and a perfect negative correlation is equal to -1.00, while a correlation of 0.00 indicates no linear relationship at all. Intermediate values indicate intermediate relationships.

The table of p-values indicate how likely this result would be, based on chance alone. Low p-values mean that the result is very unlikely to be a chance occurrence. P-values of less than 0.05 are conventionally considered “low enough” to provide strong evidence of a true relationship, with numbers lower than 0.01 indicating very strong evidence.

Globalization Indices Correlations

I should note that in the following analysis of the relationship between globalization and Covid-19, the globalization indices do not change over the time period of the data being analyzed. So, they measure globalization tendencies in countries at the start of the pandemic. That said, it is likely that these measures will be consistent over time, especially when comparing countries against each other – i.e. countries that were most globalization-friendly at the start will tend to remain that way, even as the pandemic sweeps the world, while countries that were not highly globalized are unlikely to choose to become so during a pandemic.

Covid-19 Measures

There are a number of possible measures that could be used to estimate the intensity of the pandemic at different points in time. Some examples:

Covid Infections per million population (cumulative or interval).
Covid Cases per million population (cumulative or interval).
Covid Deaths per million population (cumulative or interval).
Covid Case Fatality Rate (cumulative or interval).

All of these have strengths and weaknesses. A major weakness is the reliability and accuracy of information collections between different countries and over time within countries. I will tend to focus on Covid Deaths per million population, as that seems likely have the best record-keeping (dead bodies are hard to ignore).

The Relationship between Globalization Intensity and the Covid-19 Pandemic

Below are a selection of graphs at various points in time (about six months apart), showing the Overall Globalization Index (the scale of which varies between about 30 and about 100) versus Deaths per Million population. The upper left hand corner of the graphs gives the R-square between these two measures, which can be thought of as the proportion of variance in the scatter-plot between these variables that can be explained by a linear relationship. In other words, how well do the points follow a straight line.

May 2020

Early in the pandemic, most countries had rather low Deaths per Million Population, though a small number hit fairly high levels quite quickly. Those tended to be the highly globalized countries, as measured by the Overall Globalization Index.
The R-square was quite low (0.0457), indicating that not much of the variance was explained by the linear relationship (also visually obvious).

November 2020

By autumn of 2020 the Deaths per Million Population had risen substantially in a lot of countries, though there were still many with very low death rates.
The R-square (0.112) had risen a fair bit, so the linear relationship was now accounting for much more of the variance. Nonetheless, there is still a lot of scatter in the graph.

June 2021

Deaths per Million Population had increased substantially (note the change in the scale of they y-axis from 0-1200, to 0-3000).
The R-square was also substantially higher (0.280), so much more of the variance is now being explained by the linear relationship.

November 2021

Deaths per Million Population continued to increase (note the change in the scale of they y-axis from 0-3000, to 0-6000).
There is now one very high outlier, at nearly 6000 Deaths per Million.
The R-square has dropped somewhat, to 0.206. This may be a seasonal effect, since at this point in time, one hemisphere will have experienced two winters, while the other has only experienced one winter. However, the differing mutational phases of the virus’s evolution may also have created this effect.

June 2022

Deaths per Million Population have continued to increase.
Several more countries have broken into the 4000 to 6000 Deaths per Million range.
The R-square has gone back up (0.265), and is now nearly the same as it was in June 2020 (0.280). This would tend to support the idea that there is a seasonal effect that is responsible for the up-and-down in the R-square values.

Time Trend of Correlation and R-Square, Globalization Indices vs Deaths per Million Population

Having looked at some individual point-in-time graphs of Overall Globalization vs Covid-19 Deaths per Million, we can now put these together on one graph, along with some other points-in-time. In addition, we can look at the relationship between the other globalization measures (Social, Economic, Political) and the Deaths per Million Population Measure.

Note that the lines for each of the globalization measures show similar trends.
For the top graph, correlation coefficients have been used, rather than R-square measures. Technically, the correlation coefficient (R) is just the square root of R-square (thus the name), so this just results in a scale effect, but the overall tendency of the graphs are similar. The next graph gives the R-Square relationship between Globalization Measures and Covid-19 Deaths per Million Population.
The correlation (and R-Square) between globalization and deaths begins at a relatively low level, rises to a much highly level within a year (i.e. in four seasons), then drops a bit, and finally rises to about the same level at the end of two full years as it had been at the end of one year.
Social Globalization had the highest correlation with Deaths, followed by Economic Globalization, then finally Political Globalization at quite a bit lower level. The Overall Globalization measure (a combination of the three other measures) is not too far off the Social Globalization measure.
So, it seems that the movement of people (Social Globalization) had the most profound effect on the spread of the pandemic, followed the movement of things (Economic Globalization). Political Globalization was not so closely tied to the pandemic, perhaps because it is a more legalistic measure and thus had less of an organic relationship with the pandemic (viruses don’t travel on treaties).

There are some other interesting globalization aspects to the Covid-19 pandemic, which I will look at in a later blog.

Some earlier Covid-19 blogs:

https://dodecahedronbooks.blogspot.com/2021/07/covid-19-cases-and-deaths-by-continent.html

https://dodecahedronbooks.blogspot.com/2021/07/covid-19-cases-by-continent-jan-2000-to.html

https://dodecahedronbooks.blogspot.com/2021/03/covid-19-vaccines-how-successfully-are.html

https://dodecahedronbooks.blogspot.com/2020/12/covid-19-vaccines-comparison-of.html

https://dodecahedronbooks.blogspot.com/2020/09/covid-19-continues-to-travel-around.html

https://dodecahedronbooks.blogspot.com/2020/07/has-covid-19-become-less-deadly.html

https://dodecahedronbooks.blogspot.com/2020/07/july-2020-update-covid-19-death-rates.html

https://dodecahedronbooks.blogspot.com/2020/05/covid-19-death-rates-correlate-highly.html

https://dodecahedronbooks.blogspot.com/2020/06/covid-19-impact-on-employment-no-impact.html

https://dodecahedronbooks.blogspot.com/2020/04/is-there-model-that-can-predict-when-to.html

https://dodecahedronbooks.blogspot.com/2020/03/estimating-fatality-rate-of-coronavirus.html

===================================================

And, here’s a more pleasant travel story than anticipating the worldwide journey of a virus.

A Drive Across Newfoundland

U.S.: https://www.amazon.com/dp/B07NMR9WM8

U.K.: https://www.amazon.co.uk/dp/B07NMR9WM8

Germany: https://www.amazon.de/dp/B07NMR9WM8

Japan: https://www.amazon.co.jp/dp/B07NMR9WM8

Canada: https://www.amazon.ca/dp/B07NMR9WM8

Australia: https://www.amazon.com.au/dp/B07NMR9WM8

India: https://www.amazon.in/dp/B07NMR9WM8

On the Road with Bronco Billy

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Tuesday, 5 July 2022

Mining Lithium from Spent Oil Wells – Imperial Oil Dives into the Briny Alberta Waters

The Globe and Mail Report on Business had a story on June 24, 2022 outlining the investment of about 6 million dollars to join a pilot project for extracting lithium from a major oil formation, once prolific but now largely depleted. That would be the Leduc formation, which was the oil-rich geologic formation in central Alberta that kicked off the oil boom in that part of western Canada. It was discovered by Imperial Oil in 1947, so they have a lot of corporate knowledge of the geology of this formation in their archives. It is worth noting that Imperial Oil is Calgary based, but is nearly 70% owned by Exxon.

The hope is that the formation will have lithium rich brine that can be used in batteries and other items essential to electrification plans around the world (see the details of an earlier blog below, which explains the science behind lithium brines and old oil wells). The oil major is partnering with a company called E3 Lithium Ltd, which has plans to spend over $600 million on a lithium extraction project near Olds, Alberta (between Calgary and Edmonton). This area is known as the Clearwater region, but the Leduc Formation has a couple of other areas that have good prospects for lithium, called Rocky and Exshaw.

E3 Lithium claims to have developed some innovative technology to extract the lithium from the brine. They also say that they will incorporate renewable energy and carbon capture, to supply the energy needed for the lithium extraction process. They hope to produce 20,000 tons of lithium hydroxiide per year, beginning in 2026. They also have plans to refine that to battery-grade lithium.

As an example of lithium needs at a practical level, a Tesla auto battery uses about 60 kilograms of lithium. So, in principle, a year’s production from this plant could provide enough lithium for about 330,000 Tesla cars. So, there is probably plenty of scope for expansion.

P.S. I have no personal stake in this project, other than scientific curiosity.

Mining Lithium from Spent Oil Wells – A Talk by University of Alberta Geology Professor Daniel Allesi

Introduction

In order to get to net zero emissions (or even to approach that goal), a great deal of energy storage will be required. That’s especially true in areas like Canada, which have long periods with little sunlight, thus making solar power infeasible for much of the year, unless ample electrical storage is available. Lithium is one of the materials that is needed for electric storage, so lithium is a strategic resource of great importance, one that is currently not that widely accessible in most of the world.

This talk about extracting lithium from brines associated with spent oil wells in Alberta, Canada was delivered by Dr. Daniel Allesi of the Department of Earth and Atmospheric Sciences at the university of Alberta, a specialist in geochemistry and geomicrobiology. It dealt with his team’s research into the development of processes to extract lithium a commercial scale and prices competitive with current supplies. The official name of the talk was “Electric Potential; Extracting Lithium from Waste in Alberta”.

Lithium Demand

Huge growth in demand is expected for lithium, especially for use in Lithium-ion batteries. Lithium is basically used in all parts of these batteries, the anode, cathode and solution.
A 9X increase in demand is expected by 2030.
But supply is having trouble keeping up, so a shortage is expected soon, by about 2025.
Thus, many more sources of supply are needed, both conventional and unconventional.
One of those unconventional sources could be brine from the Duveney Formation, an oil-bearing rock formation in Alberta.
This brine is very salty, about 5X more than sea water (at about 136K ppm).
However it also does contain a fairly decent amount of Lithium, averaging at about 55 ppm.
Some cobalt, another strategic metal is also present, though at low concentrations.

Conventional Lithium Sources

Currently, one of the main conventional source of supply are salt flats, which contain Li2CO3.
- Solar evaporation is used to concentrate brine that has been collected in evaporation ponds. This results in a lithium precipitate, with a recovery rate of 50-60% of the lithium in the brine.
- However, there are considerable environment impacts from this process. It uses a lot of water, in regions that are scarce in water. That water then becomes contaminated.
- It also takes years to months for the necessary evaporation to occur and requires a lot of sunshine. These conditions are not that common (The dry high desert area of Chile is a current main source).
Hard rock, open pit mining (granite pegmatite) is another conventional source of supply. This can produce both Li2CO3 and LiOH. There are various such mines around the world, either working or in development (e.g. Africa, Australia, U.S., Quebec, there is a possibility of an Alberta mine as well).

Alberta Lithium Potential

Alberta has many millions of tons of Lithium Carbonate bran, in underground sources.
Though these are relatively low grade sources compared to a lot of current conventional supplies, they are abundant.
One estimate is 10 million tons at $25 thousand dollars per ton, so there is potentially lots of money to be made. Some brines have high grades, up to 140 ppm.
They tend to be found in areas that have had extensive oil and gas production. Therefore, costs can be reduced as much of the infrastructure needed already exists (i.e. from the oil/gas exploration and development).
Lithium in these brines is thought to be driven by hydro-thermal volcanic activity, deep underground.

Lithium Extraction Technology for Alberta Brine

There are many options for lithium extraction, such as the use of solvents, membranes, electrolysis or selective absorption.
The basic process can be thought of in these stages:
- Drill and collect brine from underground source.
- Use direct lithium extraction process (ion exchange) to remove lithium from the brine.
- Re-inject the lithium-depleted brine back underground.
- Do some cleanup, then precipitate solid lithium from the concentrate.
Some technical details (very simplified)
- Metal beads (the sorbent) are used to adsorb lithium ions from the brine. These are manganese (III) and manganese (IV).
- The metals are dipped into the brine.
- Essentially, lithium ions are adsorbed by being selected into small regions in the metal’s crystalline structure. That is due to its small size (lithium is only the third element in the periodic table).
- This loads the metal beads with lithium.
- The metal beads (sorbent) are then rinsed in a solution to extract the lithium from the sorbent, resulting in a highly concentrated brine.
- Solid lithium is then precipitated out in ponds.
- The sorbent is then dried out for re-use, to start the cycle over again.
The process can be quick, on the scale of hours rather than months.
It can recover 80%+ of the lithium, though there are also some other products produced by the process.
Some technical/commercial issues to be worked out.
- The big problem is the need to recycle and reuse the sorbent for the economics to be competitive (sorbent is expensive).
- But, manganese is lost during the process, which is a problem as it is a key part of the sorbent.
- Though the brine is from a “free site” (a site previously used for oil and thus has ready-built infrastructure) this creates a problem. The brine is often contaminated with hydrocarbons and other unwanted substances.
- This coating of the sorbent with these oils may be part of the problem that leads to the loss of sorbent.
This is the professor’s major area of research (i.e. the need to be able to reuse the sorbent).
- For commercialization, the sorbent loss rate must be kept low, perhaps only 1% or so for each cycle of the process.
- Basically, there is a need to “clean up” the brine in order to save the sorbent. This is especially true for organics in the brine.
- One idea is to centrifuge the brine, to separate out the contaminants before mixing with the sorbent.
- Washing with a surfactant (soap, basically) may help also help in the quest to maintain and reuse the sorbent.
- Use of chlorine, peroxide or filtration (ultra fine, nano-level) are some possible approaches. But filters are expensive.
- Coating the sorbent with something like zirconium might help to protect the manganese from reduction, so less loss of useful sorbent.
H2S can also be a problem, by reducing Mn(IV) to Mn(III) or Mn(II), which are less useful sorbents. So that may need to be scrubbed.

Commercialization

Problems have been solved in the lab, but can the process be done at a commercial, industrial scale? Research on this is ongoing.
Using petrol-brine at a rate of 10K cubic meters per day, with a concentration of 80 ppm can yield 1500 tons of lithium per year.
At current prices, that is feasible, but prices are high right now, so the economics might not work at lower prices.
Economic incentives (e.g. tax breaks, subsidies) would be helpful (naturally).
One advantage in favour of the process, is that the money earned via this method could offset oil industry water storage costs, so complete cost recovery may not be necessary (though always preferable).
Another advantages is that a skilled workforce already exists in Alberta (oil/gas workers are already familiar with a lot of aspects of the overall process). Some incentives for re-training would also be useful.
Ultimately, the greatest benefit would come from producing batteries from the lithium, rather than exporting it for others to do.

World Lithium Sources (excluding Alberta lithium brine in old oil wells)

Sources:

The talk “Electric Potential; Extracting Lithium from Waste in Alberta”. By University of Alberta Talk by Professor Daniel Allesi

Alberta Brine Map and diagram: Eccles, D.R.; Berhane, H. Geological introduction to lithium-rich formation water withemphasis on the Fox Creek area of west-central Alberta (NTS 83F and 83K); Energy Resources Conservation Board, Edmonton, AB, 2011; pp 1-17.

Lithium Recovery from Hydraulic Fracturing Flowback and
Produced Water using a Manganese-Based Sorbent (Masters thesis byAdam John Seip

Wiki

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And here is a description of a (relatively) carbon-emission reduced adventure, which you can buy on Kindle (also carbon-emission reduced, compared to paper).

A Ride on the Kettle Valley Rail Trail: A Biking Journal Kindle Edition

by Dale Olausen (Author), Helena Puumala (Editor)

After reading this account, you should have a good sense of whether the trail is right for you. If you do decide to ride the trail, it will be an experience you will never forget.

Amazon U.S.: https://www.amazon.com/dp/B01GBG8JE0

Amazon U.K.: https://www.amazon.co.uk/dp/B01GBG8JE0

Amazon Germany: https://www.amazon.de/dp/B01GBG8JE0

Amazon Canada: https://www.amazon.ca/dp/B01GBG8JE0

Amazon Australia: https://www.amazon.com.au/dp/B01GBG8JE0

Tuesday, 14 June 2022

The Age of Miracles (A Father’s Day Story) – Inspirational Family Fiction, Free on Amazon June 16-20, 2022

It was my wife’s Father’s Day gift to me, so it seems only appropriate to share.

This short story (approx. 6000 words) relates a trek along a lakefront path by a grandfather and his grandson. The simple lakeside walk becomes a journey of discovery, whereby they each learn much about the other, strengthening the bond between themselves in the process. When a crisis occurs, they, along with the boy’s father and the rest of the family and friends, learn something about the mysterious forces of the universe, about life and death, and about hope for the future.

The story is set in a Northern Ontario lake community, and continues to explore the setting and characters introduced in “The Boathouse Christ”, “Where the Apple Falls” and “A Christmas Miracle at the Lake”, also by Helena Puumala.

Amazon U.S.: https://www.amazon.com/dp/B09SCV6284

Amazon U.K.: http://www.amazon.co.uk/gp/product/B09SCV6284

Amazon Germany: http://www.amazon.de/gp/product/B09SCV6284

Amazon Canada: http://www.amazon.ca/gp/product/B09SCV6284