Get CO2 emission data using Carbon Intensity API

In this article, we have explored how to get CO₂ emission data for a specified time period and for specific location. For this, we have used Carbon Intensity API and have implemented the code in Python.

Table of Content:

1. Development of API (Application Programming Interface)
2. Database Presentation
3. Preparation and Interpretation of CO₂ (carbon dioxide)
4. Final Considerations
5. References

Let us get started with "Get CO2 emission data using Carbon Intensity API".

1. Development of API(Application Programming Interface)

The API can be considered a set of standards that enable communication between platforms through a series of standards and protocols. In other words, the API works as an intermediary allowing the database to be queried or changed.

It is a server that receives simple HTTP requests and returns data provided by a company/entity. This process facilitates the analysis of available information or even allows for user interaction.

Usually, all information extracted by an HTTP and API returns in JSON format. Proper use of the API maximizes data management. This API was developed in Python language.

In the code (Figure 1), there is an import the date function from the datetime, which will stipulate the range of data that will be required (GET method).
The request library is necessary to make HTTP requests, and the JSON library decodes objects and transforms them into lists or Python dictionaries (vice versa).

from datetime import date

import requests
import json

url = "https://api.carbonintensity.org.uk/intensity"

def emission():
    emission = requests.get(url)
    emission_tax =json()["data"][0]
    return emission["intensity"]["actual"]["index"]

def period(start, end):
    return requests.get(f"{url}/{start}/{end}").json()["data"]

if __name__ == "__main__":
    for entry in period(start="2021-10-4", end="2021-10-5"):
        print("from {from} to {to}: actual_tax:{intensity[actual]} index:{intensity[index]}".format(**entry))
    print(f"{emission_tax() = }")

Figure 1. API used to query CO₂ emission data and index.

2. Database Presentation

The database used was developed by the National Grid ESO together with the Environmental Defense Fund Europe and the University of Oxford (Department of Computer Science and WWF).

According to the responsible agency^[1]:

" To estimate the carbon intensity of electricity consumed in each region, a reduced GB Network model is used to calculate the power flows across the network. This considers the active and reactive power flows, system losses, and the impendance characteristics of the network. The carbon intensity of both active power flows (gCO₂/kWh) and reactive power flows (gCO₂/kVArh) is then calculated and the CO₂ flows are attributed around the network for each 30 min period over the next several days. The carbon intensity of the power consumed in each region is then determined. The same approach is used to estimate the proportion of each fuel type consumed in each region."

The data source adopted in this article is the CO₂ Intensity (National emission) available on the Carbon Intensity API Great Britain website^[2].
Other data can also be consulted, such as:

The generated rate of CO₂ for different factors (Figure 2):

{ 
  "data":[{ 
    "Biomass": 120,
    "Coal": 937,
    "Dutch Imports": 474,
    "French Imports": 53,
    "Gas (Combined Cycle)": 394,
    "Gas (Open Cycle)": 651,
    "Hydro": 0,
    "Irish Imports": 458,
    "Nuclear": 0,
    "Oil": 935,
    "Other": 300,
    "Pumped Storage": 0,
    "Solar": 0,
    "Wind": 0
  }]
}

Figure 2. CO₂ generation rate for different energy matrices.

Types of energy matrices used in national territory and their percentage of CO₂ generated (Figure 3):

{"data":{
"from":"2021-10-12T02:30Z",
"to":"2021-10-12T03:00Z",
"generationmix":[{
"fuel":"biomass",
"perc":9.4},
{"fuel":"coal","perc":0},
{"fuel":"imports","perc":15.3},
{"fuel":"gas","perc":22},
{"fuel":"nuclear","perc":16.5},
{"fuel":"other","perc":0},
{"fuel":"hydro","perc":1.1},
{"fuel":"solar","perc":0},
{"fuel":"wind","perc":35.6}
]}
}

Figure 3. Current energy matrix and its percentage of CO₂ emissions.

Regional data, type of current energy matrix, and its contribution to CO₂ generation (Figure 4):

{"data"[{
"regionid":17,
"dnoregion":"Wales",
"shortname":"Wales",
"data":[{
"from":"2021-10-12T02:30Z",
"to":"2021-10-12T03:00Z",
"intensity":{
"forecast":193,
"index":"moderate"},
"generationmix":[{
"fuel":"biomass","perc":0.3},
{"fuel":"coal","perc":0},
{"fuel":"imports","perc":0},
{"fuel":"gas","perc":48.9},
{"fuel":"nuclear","perc":10.2},
{"fuel":"other","perc":0},
{"fuel":"hydro","perc":1.4},
{"fuel":"solar","perc":0},
{"fuel":"wind","perc":39.2}
]}
]}
]}

Figure 4. Energy matrix used in the year 2021 by the region of Wales.

All this information is essential, for example, CO₂ emission data for different energy matrices are tools for managing sustainable development policies (Figure 2).

The comparison of active matrices in the national territory (figure 3) can together the electricity generation data indicating the most efficient and least polluting matrices. And the characterization of each region (Figure 4) will provide an overview of what can and should be improved.

3. Preparation and Interpretation of CO₂ (carbon dioxide)

Using the code (Figure 1) were generated the information about CO₂ emission rate in Great Britain (Table 1) and respective index/classification(Table 2).

The code output is for the time interval between October 4th (23h30min) to October 6th (midnight) between 2017 to 2021.

Table 1. CO₂ emission rate in gCO₂/kWh generated within the stipulated range between the years 2017 to 2021

2017	2018	2019	2020	2021
128	238	197	142	124
128	238	200	144	121
128	240	208	141	121
124	237	212	140	120
118	233	212	133	112
109	230	213	128	112
107	228	220	133	110
105	226	224	140	108
101	229	216	155	101
100	240	213	171	96
111	253	204	181	106
148	267	199	202	117
173	286	205	217	130
183	294	214	223	146
192	300	214	229	156
191	309	211	228	155
186	310	202	222	154
179	307	201	217	152
172	300	196	212	151
173	306	191	207	148
162	301	189	207	146
156	297	183	205	142
151	293	178	206	136
148	279	176	201	129
149	274	174	202	124
160	276	171	201	111
160	278	169	200	105
166	278	172	197	109
170	281	174	200	106
174	287	180	210	92
186	293	179	207	99
200	295	181	201	111
216	311	184	202	120
224	318	183	200	129
235	324	181	195	134
226	327	182	195	137
226	326	178	201	139
230	328	172	199	140
230	323	172	194	138
230	327	164	189	138
224	330	152	185	134
225	326	137	168	127
209	314	129	176	115
193	304	123	141	105
179	289	119	123	92
148	286	116	110	91
142	286	117	108	82
149	290	125	106	84
143	293	130	105	83

Table 2. Index/Classification of CO₂ emission rate

LOW	MODERATE	HIGH
82-199	200-280	>= 281

Table 3 groups the classification (Table 2) and the arithmetic average of the generated CO₂ rates (Table 1).

Table 3. Approximate values of CO₂ emission rate (gCO₂/kWh) for a time interval between 2017 to 2021

YEAR	EMISSION	INDEX
2017	121	low
2018	179	moderate
2019	180	moderate
2020	285	high
2021	168	moderate

The data from Table 1 and the Excel program has generated the graph (Figure 5). It contains all information about CO₂ emission rate in each 30 minutes for energy generation in gCO₂/kWh.

In 2020 was the highest value of CO₂ generated (Table 3). Several factors may have contributed to this situation. Such as the type of energy matrix or even some unusual activity at the time.

However, to have a better understanding of the subject, more in-depth studies must be carried out.

Figure 5. Graph of CO₂ emission for the interval between 2017 to 2021.

4. Final Considerations

What is the importance of the study the CO₂ emissions in electrical energy generation?

The CO₂ high rate emission is causing a ripple effect, where the increase in global temperature is changing the climate. With this, the sea level is changing, lack of drinking water, rain, food, and pests are emerging, and consequently, a possible breakdown in society could happen soon.

One of the biggest problems is the consumption of electricity and its production. It is necessary a sustainable development, preserving green areas, studying new forms to generate clean energy, and large corporations' and society's awareness.

With this article at OpenGenus, you must have the complete idea of how to Get CO2 emission data using Carbon Intensity API.

References

^[1] Carbon Intensity API, viewed October 2021. carbonintensity.org.uk

^[2] Carbon Intensity API Great Britain - National Carbon Intensity, viewed October 2021 api.carbonintensity.org.uk