Sleeping with indoor plants


Sleeping with indoor plants: The new bedding trend. A few decades ago, it was cool to sleep on a wool rug under a sheepskin, now, you can do the same with a green plant. It’s a bedding trend that has a surprising number of advantages. Here are some of them.

1. Plants absorb CO2 and filter particles.

CO2 is a greenhouse gas that’s more than 30 times more powerful than carbon dioxide. It’s produced by combustion of fossil fuels, animal or other agriculture activities, or by human activities such as driving and heating buildings. According to the Global Environmental Facility, CO2 accounts for a third of all greenhouse gas emissions, and contributes to climate change.

While the greenhouse gases released into the atmosphere from our combustion of fossil fuels are increasing daily, the atmospheric concentration of CO2 has actually dropped slightly over the last decade. This is largely a result of the increasing usage of biogas in power plants, rather than fossil fuels. But the atmospheric concentration of CO2 is still much higher than it was just a decade ago.

The plants in your home are, however, a significant carbon sink. In an article in Scientific American, a study compared how much CO2 various common types of plants are able to absorb. The authors compared leaf structure, the ability of the plant to photosynthesize, and the size of the plant (shoots, leaves, roots) to determine how much CO2 plants were able to absorb. The table below shows what was found in their study.

CO2 absorption efficiency of common indoor plants

Plant

Photosynthetic Efficiency

Percent Carbon Absorbed

Water absorption

Percent Carbon Absorbed

Water absorption

Alfalfa

14.2

14.3

0.3

0.4

Aster

9.2

7.2

0.6

1.7

Aquatic plants

4.8

3.4

0.7

1.7

Bean

3.1

6.3

0.3

0.3

Bulrush

7.5

0.5

1.5

2.4

Buckwheat

12.4

1.6

1.3

0.6

Canna

5.4

2.1

0.7

0.5

Celery

14.7

0.3

1.3

0.6

Duckweed

8.7

0.6

0.6

0.3

Goldenrod

7.8

0.7

0.3

0.4

Hare

0.8

0.1

0.1

0.4

Hemlock

7.1

0.1

0.7

0.5

Lagoon

12.2

1.5

1.2

0.7

Lagoon

23.5

2.4

0.8

0.7

Lotus

3.2

1.8

0.3

0.5

Maiden hair

0.4

0.3

0.3

0.2

Mugwort

3.6

0.4

1.1

0.4

Nasturtium

1.2

0.6

0.1

0.5

Nymphs

0.4

0.1

0.3

0.3

Onion

0.7

0.3

0.2

0.3

Peach

0.1

0.2

0.2

0.2

Peony

0.4

0.1

0.2

0.3

Red Clover

0.6

0.3

0.1

0.1

Tick

0.2

0.2

0.2

0.1

Vines

0.8

0.3

0.3

0.2

Vine

0.3

0.2

0.2

0.2

Vine Rope

0.2

0.1

0.2

0.1

The most interesting results for me here are

the very low counts of Peony. All other plants were recorded in some

percentage of samples. It also surprises me that there are no

significant differences between the

plant samples in the organic and non-organic fields. I will try to

understand what that means in the future.

The same data was now collected in a new field, the

Glyzer field. Here, the sample numbers are somewhat larger (30

samples for organic and 20 samples for non-organic), but the

variation between the sample numbers is no longer as big.

So

far it seems the difference between organic and non-organic fields is

only in degree. We did not find any significant differences between

the fields in the chemical data that we studied, not even in the case

of the number of fungi.

The most interesting result in the organic field is that the

number of Peony is much higher in the organic field, while this is

not the case in the non-organic field.

Since the plant numbers in the organic and the

non-organic fields are so similar, it is very likely that the

difference in the number of Peony is caused by the difference in the

amount of nitrogen and potassium fertilizers.

For the first three weeks the growth rate of

the plants in the organic and non-organic field was almost the same.

At the moment the growth rate of the plants in the organic field is

slower than in the non-organic field.

For this experiment I decided to not take samples from

the edge of the field, but from some places in the middle. A

compartment of plants of each species was taken and dried, and the

dry masses of the plants were added together. Then the plants were

mixed up, and a sample was taken. The total mass of plants was

compared to the mass of the samples, and the ratio was used to

calculate the growth rate of the plant during the week.

The

growth rate of the plant species was compared using a two-way ANOVA

with the number of years, and with the sample type (organic or

non-organic field), as factors.

Since the differences between the two factors was

very small, the two-way ANOVA analysis was not sufficient to

separate these two factors. So the mean and standard error of the

difference between the sample types for each years were used to

compare these sample types.

The analysis showed that there was no

difference in the plant growth rate between the organic and non-

organic fields. But the plant growth rate was the same for every

year. It



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