Particulate Matter (PM) Pollution Plummets

I) Particulate Matter Drops by 75.54% to 26,760 Metric Tonnes

A) About the data

The particulate matter (PM) data was obtained from sustainability reports (BRSR), in form of XML files, of the respective companies in the BSE 30 domain from the web. The data needed to be worked upon. I am showing two data tables at the end of the blog post. The first one is the data as was reported, and the second one is with a column added at the end showing the change in percentage values in the two years - FY 22 to FY 23.

B) What is the data on particulate matter, saying?

Analysing the business responsibility and sustainability reports (BRSR) of BSE 30 companies in India, reveal considerable decrease in particulate matter (PM) in FY23. and largely the decreases is because of NTPC.

NTPC's particular matter (PM) discharge was down by -89.80%.

The total particulate matter (PM) in FY 23 was at 26,760 metric tonnes a drop off -75.54 percent from 109,383 metric tonnes in FY 22.

The top three producers of particulate matter (PM) for both FY 23 and FY 22 were companies in manufacturing industry namely Tata Steel, NTPC and Ultra Tech cement.

In FY 23, these three companies accounted for almost 88% of the particulate matter (PM) discharge.

JSW steel would have been there, but I couldn't calculate their particulate matter (PM) discharge because of the unfamiliar denominator

A lot of companies reported particular matter, PM as zero.

C) Why it matters to monitor particulate matter (PM)?

In the video, Harvard Professor David Keith explains particulate matter (PM), which shortens lifespan substantially.

PM2.5 concentration in Mumbai, India is currently 26.2µg/m³ and is 5.2 times the WHO annual air quality guideline value.

PM2.5 concentration in Pune, India is currently 24.3µg/m³ and is 4.9 times the WHO annual air quality guideline value. It is explained on the AQI web site.

To know air-quality in any city in India, please click on the AQI link

D) My earlier blog posts on the subject

• Kindly refer to my last year's blog post on particulate matter PM.

• Also refer to my earlier links to posts on NOX and SOX emissions.

E) Conclusion

The data in the BRSR sustainability reports, is a valuable source of information. By going through the data reveals a lot of information. However, the challenge continues to be inconsistent data, missing data and data with different units, thereby working on it becomes difficult. I hope the quality of the data improves as we go along.

F) Data Tables

F1) Data Table 1 particulate matter PM data as downloaded

	nameofthecompany	unitofparticulatematter FY23	unitofparticulatematter FY22	particulatematter FY23	particulatematter FY22
0	Bharti Airtel	Metric Tonnes	Metric Tonnes	15	19
1	Larsen & Toubro	mg/m3	mg/m3	10	4
2	State Bank of India	0	0	0	0
3	HCL Technologies	0	0	0	0
4	JSW STEEL	kg/tcs	kg/tcs	0.42	0.488
5	Wipro	Mg/Nm3	Mg/Nm3	49.6	50.5
6	Reliance Industries	Tonnes	Tonnes	1659	1722
7	Tata Motors	Metric Tonne	Metric Tonne	577	789
8	Power Grid Corporation of India	Not Applicable	Not Applicable	0	0
9	Maruti Suzuki India	mg/Nm3	mg/Nm3	Less than 50 mg/Nm3 for incinerator	Less than 50 mg/Nm3 for incinerator
10	Mahindra & Mahindra	tCO2e	tCO2e	15.99	8.98
11	ICICI Bank	Not applicable	Not applicable	Not applicable	Not applicable
12	Titan Company	μg/m³	μg/m³	586.58	568.83
13	Sun Pharmaceutical Industries	MT	MT	142	214
14	Axis Bank	NA	NA	0	0
15	Kotak Mahindra Bank	tCO2e	tCO2e	0	0
16	Asian Paints	SPM (g)	SPM (g)	10.48	12.19
17	NTPC	Metric tonnes	Metric tonnes	9294.96	91115.34
18	Hindustan Unilever	Mg/Nm3	Mg/Nm3	55	61
19	Tech Mahindra	tons	tons	0.217	0.806
20	IndusInd Bank	0	0	0	0
21	Bajaj Finserv	0	0	0	0
22	UltraTech Cement	Tonnes	Tonnes	3227.46	2873
23	Infosys	Kg	Kg	3441.52	3899.34
24	Bajaj Finance	0	0	0	0
25	Tata Consultancy Services	0	0	0	0
26	ITC	Tonnes	Tonnes	825	637
27	Tata Steel	Kilotonnes/year\n	Kilotonnes/year\n	11	12
28	Cipla	mg/Nm3	mg/Nm3	29.6	30.74
29	HDFC Bank	0	0	0	0

F2) Data Table 2 particulate matter PM with change % column added.

	nameofthecompany	unitofparticulatematter FY23	unitofparticulatematter FY22	particulatematter FY23	particulatematter FY22	change PC
0	Bharti Airtel	Metric Tonnes	Metric Tonnes	15.000	19.000	-21.05
1	Larsen & Toubro	mg/m3	mg/m3	10.000	4.000	150.00
2	State Bank of India	0	0	0.000	0.000	NaN
3	HCL Technologies	0	0	0.000	0.000	NaN
4	JSW STEEL	kg/tcs	kg/tcs	0.420	0.488	-13.93
5	Wipro	Mg/Nm3	Mg/Nm3	49.600	50.500	-1.78
6	Reliance Industries	Tonnes	Tonnes	1659.000	1722.000	-3.66
7	Tata Motors	Metric Tonne	Metric Tonne	577.000	789.000	-26.87
8	Power Grid Corporation of India	Not Applicable	Not Applicable	0.000	0.000	NaN
9	Maruti Suzuki India	mg/Nm3	mg/Nm3	NaN	NaN	NaN
10	Mahindra & Mahindra	tCO2e	tCO2e	15.990	8.980	78.06
11	ICICI Bank	Not applicable	Not applicable	NaN	NaN	NaN
12	Titan Company	μg/m³	μg/m³	586.580	568.830	3.12
13	Sun Pharmaceutical Industries	MT	MT	142.000	214.000	-33.64
14	Axis Bank	NA	NA	0.000	0.000	NaN
15	Kotak Mahindra Bank	tCO2e	tCO2e	0.000	0.000	NaN
16	Asian Paints	SPM (g)	SPM (g)	10.480	12.190	-14.03
17	NTPC	Metric tonnes	Metric tonnes	9294.960	91115.340	-89.80
18	Hindustan Unilever	Mg/Nm3	Mg/Nm3	55.000	61.000	-9.84
19	Tech Mahindra	tons	tons	0.217	0.806	-73.08
20	IndusInd Bank	0	0	0.000	0.000	NaN
21	Bajaj Finserv	0	0	0.000	0.000	NaN
22	UltraTech Cement	Tonnes	Tonnes	3227.460	2873.000	12.34
23	Infosys	Kg	Kg	3441.520	3899.340	-11.74
24	Bajaj Finance	0	0	0.000	0.000	NaN
25	Tata Consultancy Services	0	0	0.000	0.000	NaN
26	ITC	Tonnes	Tonnes	825.000	637.000	29.51
27	Tata Steel	Kilotonnes/year\n	Kilotonnes/year\n	11.000	12.000	-8.33
28	Cipla	mg/Nm3	mg/Nm3	29.600	30.740	-3.71
29	HDFC Bank	0	0	0.000	0.000	NaN

SOx Emissions Increase by 8PC in FY23

Indian Companies' SOx Emissions Increase : NTPC by 95.4%

Summary

SOX emissions of top BSE 30 Indian companies increased by 8.3% in FY 23 over FY 22 to 18,53,065 from 17,11,153 in Metric Tonnes. NTPC, the largest thermal electricity producer, accounted for 95.4% of the SOX emissions for year FY 23. Tata steel was the second largest emitter of SOX. JSW steel reported data that I couldn't use.

This is further to my blog post on analysis of NOx emissions.

Why Report on SOx Emissions? 

Sulphur oxides (SOx), primarily in the form of sulphur dioxide (SO2), have significant impacts on both the environment and human health and hence listed companies report on SOx emissions in their sustainability reports.

SOx emissions contribute to climate change and harm the environment. Reporting these emissions is part of Environmental, Social, and Governance (ESG) disclosure. It helps identify deficiencies or weaknesses in a company’s internal controls and is crucial for transparency and integrity in reporting processes.
SOX emissions of BSE 30 companies in India

I downloaded data of these companies from their business responsibility and sustainability report reporting (BRSE) in form of XML files.
The data

The downloaded data in HTML table format looks like this. To it I added a column in the end named change PC showing the change in FY23 over FY22 in %.

The first impression of the data

• The data was reported in different units. 
• Following companies didn't report the data. 

The following 10 companies reported data as zero ['State Bank of India', 'HCL Technologies ', 'Power Grid Corporation of India ', 'Axis Bank ', 'Kotak Mahindra Bank ', 'IndusInd Bank ', 'Bajaj Finserv ', 'Bajaj Finance ', 'Tata Consultancy Services ', 'HDFC Bank ']



• The following two companies provided data as a text comment.

['Maruti Suzuki India ', 'ICICI Bank ']

• The maximum increase in value in  % was 52.27 (associated with Mahindra & Mahindra).
• The maximum decrease in change value in  % was -90.20 (associated with Tech Mahindra).
• Top 3 companies with maximum increase were:

- Mahindra & Mahindra : 52.27

- Larsen & Toubro : 50.00

- UltraTech Cement : 34.36

These are increases and hence are not good values. 

• Top 3 companies with maximum decrease were:

- Infosys : -56.12

- Tata Motors : -68.67

- Tech Mahindra : -90.20

These are reductions and hence are good values.

Normalised data

I normalised the data in metric tonnes. The calculation is shown below. 

For the conversion factors, I used standard metric conversions. Here are the sources for each conversion:

• Metric Tonnes, Tonnes, Metric Tonne, MT: These are already in Metric Tonnes, so no conversion is needed.
• mg/m3 to Metric Tonnes: 1 mg = 1e-6 kg, 1 m3 = 1e-3 m3 (assuming standard temperature and pressure), so 1 mg/m3 = 1e-9 Metric Tonnes.
• kg/tcs to Metric Tonnes: 1 kg = 1e-3 Metric Tonnes, so 1 kg/tcs = 1e-3 Metric Tonnes/tcs.
• Kg/day to Metric Tonnes/year: 1 Kg/day = 365 Kg/year = 365e-3 Metric Tonnes/year.
• μg/m³ to Metric Tonnes: 1 μg = 1e-9 kg, 1 m3 = 1e-3 m3 (assuming standard temperature and pressure), so 1 μg/m³ = 1e-12 Metric Tonnes.
• tons to Metric Tonnes: 1 ton (US ton) = 0.907185 Metric Tonnes, so 1 ton = 0.907185 Metric Tonnes.
• tCO2e to Metric Tonnes: 1 tCO2e = 1 Metric Tonnes (by definition of tCO2e).
• SO2 (g) to Metric Tonnes: 1 g = 1e-6 Metric Tonnes, so 1 SO2 (g) = 1e-6 Metric Tonnes.
• Metric tonnes to Metric Tonnes: These are the same, so no conversion is needed.
• Kg to Metric Tonnes: 1 Kg = 1e-3 Metric Tonnes, so 1 Kg = 1e-3 Metric Tonnes.
• Kilotonnes/year to Metric Tonnes: 1 Kilotonne/year = 1e3 Metric Tonnes/year, so 1 Kilotonne/year = 1e3 Metric Tonnes/year.
• mg/Nm3 to Metric Tonnes: 1 mg = 1e-6 kg, 1 Nm3 = 1 m3 (assuming standard temperature and pressure), so 1 mg/Nm3 = 1e-9 Metric Tonnes.

Please note that these conversions assume standard temperature and pressure and may not be accurate for all situations. Also, the conversion from Kg/day to Metric Tonnes/year assumes 365 days in a year, which may not be accurate for leap years. You may need to adjust these conversion factors based on your specific needs.

While it was an effort to normalise the data, it was worth it. Now you can compare values. Please note in the calculation JSW steel was omitted. The reason was the denominator had a unit which is about units of steel production. In the context of emissions and industrial processes, "tcs" in "kg/tcs" typically stands for "tonnes of crude steel". This unit is often used in the steel industry to measure emissions per tonne of steel produced. So, "kg/tcs" would mean "kilograms per tonne of crude steel". This allows for a standardized measurement of emissions that accounts for the scale of production. Please note that the exact meaning can vary depending on the specific context and industry. It's always a good idea to refer to the original source or context for the most accurate interpretation.I couldn't convert it into million tonnes as I have done with others, so the total SOx would be higher.

The normalised data table

All the units are in Metric Tonnes

The conclusion

While this data set offers some insights, drawing definitive conclusions was challenging due to missing information, inconsistencies in how (units) data was reported, and instances of unusable data. A more comprehensive and standardized data collection and reporting effort is recommended.

NOx Emissions: A Data-Driven Analysis

NOx data analysis

Background

I have been analysing sustainability data for top 30 Indian companies. I have chosen to read the sustainability reports in XML files available in public domain. Filing of this report is mandatory. I have been looking at completeness and accuracy of the data, And what we can make out of it.In this blog I am focusing on NOx emissions.

I've been writing about it for a while now. You can refer to my last blog post here.

I've been also writing on the subject on LinkedIn. Here is the Linkedin post.

Causes of NOx Emissions:

NOx emissions, which include nitric oxide (NO) and nitrogen dioxide (NO2), are primarily produced from the reaction between nitrogen and oxygen during the combustion of fuels, such as hydrocarbons, especially at high temperatures. This typically occurs in car engines, power plants, and industrial boilers. Natural sources of NOx emissions include lightning and biogenic sources. source: wikipedia

Leading Data Points on NOx Emissions:

Nitrous oxide emissions have been measured in tonnes of carbon dioxide-equivalents over a 100-year timescale3. source: oneworldindata

Data as pulled from the files

As the table is long, I am not showing the entire table. Instead, I am showing tables with a calculated column at the end, and by splitting the table into smaller tables as shown below. The tables are split according to the units in which the data is reported. The last column is increase in FY 23 value over FY 22 value in percentage for each company.

The entire table is available on my twitter post.

As you can see, the data is reported in 18 different units by 30 companies.

• Metric Tonnes
• 0
• kg/tcs
• mg/Nm3
• Tonnes
• Metric Tonne
• Not Applicable
• ppm
• tCO2e
• Not applicable
• μg/m³
• MT
• NA
• NOx (g)
• Metric tonnes
• tons
• Kg
• Kilotonnes/year

Data analysis with % change column calculated and added at the end by me

1. Companies that have reported data in Metric Tonnes

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
17	NTPC	Metric tonnes	Metric tonnes	657376.38	640419.16	2.65

2. Companies that have reported data in 0

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
1	Larsen & Toubro	0	0	0.0	0.0	NaN
2	State Bank of India	0	0	0.0	0.0	NaN
3	HCL Technologies	0	0	0.0	0.0	NaN
20	IndusInd Bank	0	0	0.0	0.0	NaN
21	Bajaj Finserv	0	0	0.0	0.0	NaN
24	Bajaj Finance	0	0	0.0	0.0	NaN
25	Tata Consultancy Services	0	0	0.0	0.0	NaN
29	HDFC Bank	0	0	0.0	0.0	NaN

3. Companies that have reported data in kg/tcs

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
4	JSW STEEL	kg/tcs	kg/tcs	1.19	1.26	-5.56

4. Companies that have reported data in mg/Nm3

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
5	Wipro	mg/Nm3	mg/Nm3	258.60	240.80	7.39
28	Cipla	mg/Nm3	mg/Nm3	49.09	36.63	34.02

5. Companies that have reported data in Tonnes

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
6	Reliance Industries	Tonnes	Tonnes	34337.00	36991.00	-7.17
22	UltraTech Cement	Tonnes	Tonnes	84169.11	73717.33	14.18
26	ITC	Tonnes	Tonnes	2382.00	1799.00	32.41

6. Companies that have reported data in Metric Tonne

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
7	Tata Motors	Metric Tonne	Metric Tonne	92.0	247.0	-62.75

7. Companies that have reported data in Not Applicable

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
8	Power Grid Corporation of India	Not Applicable	Not Applicable	0.0	0.0	NaN

8. Companies that have reported data in ppm

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
9	Maruti Suzuki India	ppm	ppm	NaN	NaN	NaN

9. Companies that have reported data in tCO2e

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
10	Mahindra & Mahindra	tCO2e	tCO2e	11.68	4.38	166.67
15	Kotak Mahindra Bank	tCO2e	tCO2e	0.00	0.00	NaN

10. Companies that have reported data in Not applicable

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
11	ICICI Bank	Not applicable	Not applicable	NaN	NaN	NaN

11. Companies that have reported data in μg/m³

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
12	Titan Company	μg/m³	μg/m³	133.15	132.9	0.19

12. Companies that have reported data in MT

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
13	Sun Pharmaceutical Industries	MT	MT	126.0	166.0	-24.10
18	Hindustan Unilever	MT	MT	315.0	317.0	-0.63

13. Companies that have reported data in NA

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
14	Axis Bank	NA	NA	0.0	0.0	NaN

14. Companies that have reported data in NOx (g)

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
16	Asian Paints	NOx (g)	NOx (g)	40.28	42.43	-5.07

15. Companies that have reported data in Metric tonnes

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
17	NTPC	Metric tonnes	Metric tonnes	657376.38	640419.16	2.65

16. Companies that have reported data in tons

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
19	Tech Mahindra	tons	tons	0.75	3.268	-77.05

17. Companies that have reported data in Kg

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
23	Infosys	Kg	Kg	26015.1	22907.32	13.57

18. Companies that have reported data in Kilotonnes/year

	nameofthecompany	unitofnox FY23	unitofnox FY22	nox FY23	nox FY22	change PC
27	Tata Steel	Kilotonnes/year\n	Kilotonnes/year\n	30.0	32.0	-6.25

My analysis

Analysis:

Decrease in Emissions: Several companies have shown a ▼ decrease in NOx emissions from FY22 to FY23. For instance, Bharti Airtel has reduced its emissions by 9.44%, JSW STEEL by 5.56%, and Reliance Industries by 7.17%. The most significant reduction is seen in Tata Motors with a decrease of 62.75%.

Increase in Emissions: Some companies have shown an ▲ increase in NOx emissions. Wipro’s emissions increased by 7.39%, and Mahindra & Mahindra’s emissions increased significantly by 166.67%. ITC and Cipla increased by 30% plus. UltraTech Cement and Infosys also saw an increase in emissions by 14.18% and 13.57% respectively.

No Emissions Data: Several companies such as Larsen & Toubro, State Bank of India, HCL Technologies, and others have no data available for NOx emissions. So also Power Grid Corporation of India, ICICI bank and Axis Bank didn't report on the data.

Conclusion:

The data shows a mixed trend in NOx emissions among India’s top 30 companies. While some companies have made significant strides in reducing their NOx emissions, others have seen an increase. This highlights the need for continued efforts and innovative strategies to reduce NOx emissions across all sectors. It also underscores the importance of transparency and accurate reporting in tracking progress towards sustainability goals.

Waste Management by top Indian companies

“Recycling leads with 98.22% median value”

A) Data:

I analysed waste management for BSE 30 companies based on the BRSR data they had filed with the regulator in form of XML/XBRI files. The data is for FY 23 and FY 22.

B) Introduction:

In an era where sustainability is no longer a choice but a necessity, understanding how companies manage their waste has become crucial. This post delves into the waste management practices of BSE 30 companies, based on the BRSR data they filed with the regulator for FY 23 and FY 22. We’ll explore the different types of waste generated, the proportions of each type, and how these companies are recycling, reusing, and recovering waste.

The PDF with visualisations is available in my LinkedIn post.

And my earlier blog post on waste management for the last year. 

C) Part I Waste Management

The data is presented under following heads. Total Waste generated (in metric tonnes)

Plastic Waste (A)

It was a small percentage for almost all companies.

E-waste (B)

This component of the total was hundred percent for following companies. IndusInd Bank, Bajaj finance, Bajaj Finserv, HDFC bank. It was close to hundred percent for Axis bank.

Bio-medical waste (C)

It was almost 0 for all the companies.

Construction and demolition waste (D)

It looks like this activity had picked up during the year FY 23. It was close to hundred percent for Tata Consultancy Services. It was more than 50% for L&T, Infosys and NTPC.

Battery waste (E)

Tech Mahindra, HCL Technologies and Bharati Airtel reported more than 30% for this category.

Radioactive waste (F)

Thankfully, it was zero for almost all companies. An IT company reported a very small percentage.

Other Hazardous waste. Please specify, if any. (G)

It was more than 50% for the two pharmaceutical companies.

Other Non-hazardous waste generated (H).

Please specify, if any. (Break-up by composition i.e., by materials relevant to the sector)

Other non-hazardous waste occupies big part of total waste generated for almost all companies. Its median value was 71.25%. Classifying as such under others doesn't give much information. Sustainability leaders and regulators should ponder over this point.

Total (A+B + C + D + E + F + G + H)

Let me explain with an example. In case of Wipro for year FY23, the total waste generated was 4.48K metric tonnes. 55% of it was other non-hazardous waste, 34.4% was construction and demolition waste, and the rest was made up of e waste, plastic waste, battery waste, biomedical waste, and other hazardous waste. and c) Wipro e-waste was 5.9% of its total waste, whereas that of Infosys was only 3.9% of its total waste.

Median value of total waste generated was 24,068.8 in metric tonnes. The highest for a company was 20.23 MMT.

D) Part II Recycle, Reuse and Recover (RRR)

For each category of waste generated, total waste recovered through recycling, re-using or other recovery operations (in metric tonnes)

Three companies reported zero for the total waste recovered in FY23 & in FY22 (and no data on sub categories of recovery ) and similarly 2 companies in FY22. Is this the case of missing data?

(i) Recycled

Waste recycling appears to be preferred approach. Its median value in FY23 was 98.22% which is quite impressive.

These companies reported hundred percent recycling for both the years: L&T, Tata consultancy services, JSW steel Ltd, State Bank of India and Tata motors. This is really impressive.

(ii) Re-used

In FY23 more than 50% of companies reported 0% on reuse. While others had a very small number for reuse.

But two companies out for doing hundred percent re use mainly power grid Corporation of India and Titan company.

(iii) Other recovery operations

In FY23 more than 50% of companies did not opt for “other recovery, methods” for recovery which is good because “other method” wouldn’t give any information.

For each category of waste generated, total waste disposed by nature of disposal method (in metric tonnes) is reported as follows.

Four companies reported zero for total waste disposed (and no data on sub categories) in FY 23 and similarly, seven in FY 22.

(i) Incineration

Two companies reported hundred percent, and one came close to hundred percent in FY 23 under this category and one in FY 22.

Five companies reported more than 50% under this category for both the years.

(ii) Landfilling

Landfilling appears to be more preferred choice. 41.01% was the median value for it. It was 67.38% in FY22. 90 to 100% of waste (of the total waste disposed in FY23) was sent to landfill by eight companies, out of 30.

(iii) Other disposal operations

Six companies reported hundred percent under this category. Similarly, four FY 22.

As I said earlier, this doesn't clarify, what was the method.

Total

If I categorise the total waste generated into a) total recovered and b) total disposed, then I get the following analysis.

Median value of total waste recovered in FY23 in % was 71.81. This is a good number. The focus appears to be recovering of the waste.

The data was read using a Python script. Reading multiple machine readable XML files and gathering relevant specific data using a Python script helped.You can read the data across the companies. But you cannot compare it as there is no common base.

E) Conclusion

In conclusion, the analysis of BSE 30 companies’ waste management practices reveals a diverse landscape. While some companies have shown impressive strides in recycling and reusing waste, others have room for improvement. The high percentage of ‘Other Non-hazardous waste’ across companies calls for more transparency and specificity in waste categorization. Furthermore, the zero recovery reported by some companies raises questions about data completeness.

As we move forward, it’s clear that more consistent and detailed reporting, coupled with innovative waste management strategies, will be key to achieving our sustainability goals. Let’s hope that this analysis sparks conversations and actions towards better waste management in our corporate sector.

GHG emissions data from 3 leading Indian IT companies

GHG Emissions plus SOx, NOx, and Particulate Matter (PM) Data - From 3 leading Indian IT companies

Background

Section-I

Details of greenhouse gas emissions (Scope 1 and Scope 2 emissions) and its intensity:

Description of Scope 1 and Scope 2 Emissions

"Scope 1 emissions are direct greenhouse (GHG) emissions that occur from sources that are controlled or owned by an organization (e.g., emissions associated with fuel combustion in boilers, furnaces, vehicles). Scope 2 emissions are indirect GHG emissions associated with the purchase of electricity, steam, heat, or cooling. Although scope 2 emissions physically occur at the facility where they are generated, they are accounted for in an organization’s GHG inventory because they are a result of the organization’s energy use." - Source EPA

Greenhouse gas emissions (Scope 1 and Scope 2 emissions) and its intensity

Unit for Data on Total Scope 1 and Scope 2 emissions is Metric tonnes of CO2 equivalent.

The data was read using XML/XBRL for Scope 1 and 2 emissions. It was inline with data read manually from PDF file.

A) Scope 1: Infosys gave break up of Total Scope 1 emissions (Break-up of the GHG into CO2, CH4, N2O, HFCs, PFCs, SF6, NF3, if available) in its PDF format document.

C) Scope 1 and 2 per Rs Turnover and F) Scope 3 per Rs Turnover: HCL reported it per Rs million, whereas Infosys per Rs Cr. MindTree reported in per Rs hence its ratio was very small and was shown as zero.

This was also observed in intensity calculations related to electricity in my earlier blog post.

D) Scope 1 and 2 intensity MindTree reported it in Metric tonnes of CO2 equivalent per square feet. The other two companies did not.

Please see the data table below.

Description of Scope 3 Emissions

"Scope 3 emissions are the result of activities from assets not owned or controlled by the reporting organization, but that the organization indirectly affects in its value chain. Scope 3 emissions include all sources not within an organization’s scope 1 and 2 boundary. The scope 3 emissions for one organization are the scope 1 and 2 emissions of another organization. Scope 3 emissions, also referred to as value chain emissions, often represent the majority of an organization’s total greenhouse gas (GHG) emissions."

"The GHG Protocol defines 15 categories of scope 3 emissions, though not every category will be relevant to all organizations. Scope 3 emission sources include emissions both upstream and downstream of the organization’s activities."

Figure Scope 1, 2 and 3 expalined (Source EPA)

Scope 1, 2, and 3 emissions explained by EPA, USA

"Emissions-wise, Scope 3 is nearly always the big one."

G) Scope 3 intensity: MindTree reported it in Metric tonnes of CO2 equivalent per square feet. The other two companies did not.

E) Scope 3: The script returned NaN for Infosys even though the number was typed in and present. I suspect the number was typed and formatted manually by adding thousand separators. I had to replace that number without thousand separators and it worked.

I keep highlighting issues on organising data in spreadsheets. Please refer to my earlier blog on it.

Data Table for Scope 1, 2, and 3 emissions

GHG Scope 1, 2, 3  emissions data of leading Indian companies

Waste Management - Data from 3 leading Indian IT companies

Essential Indicators - Waste Management

Background

Continuing with my last blog on scrapping (reading) data from XML, XBRL files, here I am presenting to you data collected on Waste Management.

The data is presented in a table in two parts as per the standard template of BRR.

The data is also plotted in simple bar charts in two parts and are at the bottom of this post. The bar charts help you grasp the numbers.

Part I Waste Management

The data is presented under following heads.

Total Waste generated (in metric tonnes)

Plastic Waste (A)

E-waste (B)

Bio-medical waste (C)

Construction and demolition waste (D)

Battery waste (E)

Radioactive waste (F)

Other Hazardous waste. Please specify, if any. (G)

MindTree has given the break up for the following.

Tube Lights, CFL Bulbs, Used Oil, Oil-soaked cotton waste - DG Filters, Printing Ink/Cartridges

Other Non-hazardous waste generated (H). Please specify, if any. (Break-up by composition i.e., by materials relevant to the sector)

Again MindTree has given the break up as follows.

Inorganic Waste, Organic Waste, Packaging Waste - Others

Total (A+B + C + D + E + F + G + H)

The total reported by Infosys in its human readable PDF format is 8,091.25, which is different. Please see the table below.

Part II Recycle, Reuse and Recover (RRR)

For each category of waste generated, total waste recovered through recycling, re-using or other recovery operations (in metric tonnes)

(i) Recycled

HCL has given a comment which says "100% recycled for battery and hazardous waste."

(ii) Re-used

(iii) Other recovery operations

Total

For each category of waste generated, total waste disposed by nature of disposal method (in metric tonnes) is reported as follows.

(i) Incineration

(ii) Landfilling

(iii) Other disposal operations

Total

The data was read using a Python script and presented below. You can read the data across the companies.

But you can not compare it as there is no common base.

Data Table

Charts Waste Management

Charts Recycle, Reuse and Recover

Conclusion

Reading multiple machine readable XML files and gathering relevant specific data using a Python script helped. The data was gathered quickly and without any errors. This is the first step. Once you have the data, then analysis of the data can be done.

Water consumption data of 3 leading Indian IT companies

Water Consumption Data of 3 leading Indian IT companies. 

Background:

Kindly refer to my last blog post which was about scrapping energy data, from xml file containing Business Responsibility Report in machine readable XBR language, of 3 leading Indian companies namely MindTree, Infosys and HCL.

About this post:

This post reads data from the same xml file and XBRL on how much water was drawn from various sources and how much was consumed from water consumption data of 3 leading Indian IT companies. 

The two visualisations at the end show all the data (in absolute and percentages) in bar charts for ease of reading and understanding. 

Let us begin. The xml and XBRL file was read using Python script and data was plotted using Matplotlib.

Section - I)

Water withdrawal by source (in kilolitres) 

i) Surface water

Apparently only MindTree used surface water. 29% of the total water consumption of MindTree was from surface water.  The other two companies didn’t.

(ii) Groundwater

It is the other way round. MindTree didn’t use ground water, but the other two companies did. Infosys usage was 45% of its total water consumption. It was 9% of usage in case of HCL.

(iii) Third party water 

Third party water was used by all. From the human readable BRR, you can see the break up of third party water for MindTree namely water from municipal corporation, private sources and packaged water. The other two companies didn’t give any further break up.  

MindTree usage was 64%, Infosys used 86% whereas it was 33% for HCL.

(iv) Seawater / desalinated water

The usage of it was zero or not applicable for all the three companies. 

(v) Others

In case of MindTree (6% of its total) and Infosys (5% of its total) this source was rainwater. In case of HCL (22% of its total) it included rainwater plus municipal water. 

Total volume of water withdrawal (in kilolitres) (i + ii + iii + iv + v )

This was total of all the above sources.

Total volume of water consumption (in kilolitres)

The water consumption was equal to water withdrawal for MindTree and Infosy. But water consumed was 97% and was lower compared with water withdrawn in case of HCL. 

Water intensity per rupee of turnover (Water consumed / turnover) 

Unlike last time, I did not do any calculation on my own. Infosys reported WI with Rs Crore in the denominator, while HCL reported the WI with Rs Million in the denominator. WI of HCL can be compared with that of Infosys by multiplying it by 10. MindTree reported zero.

Water intensity (optional) 

MindTree reported it by using area in the denominator but the other two companies didn’t. 

Section - II)

Water Discharge

Water discharge has to be reported on all the parameters mentioned above for water sources with additional information on discharge mentioning if the discharge was treated before discharge.

  

MindTree reported zero liquid discharge for all its sites by 100% recycling. 

Similarly Infosys reported no discharge in any of these categories. Infosys  treated Waste water generated in sewage treatment plants and reused for purposes like landscaping, HVAC applications and flushing. 

HCL reported a discharge of 23,453.06 kilolitres that was sent to third parties with no treatment.

Chart showing water consumption absolute numbers

Chart showing water consumption percentage wise

Conclusion

Thus it is convenient to read and extract data from xml and xbrl machine-readable Business Responsibility Report (BAA). This approach reduces the errors introduced in manually copying and pasting the data. This was the very purpose of introducing this format. 

Energy Consumption Data from Business Responsibility Report (BRR) and XBRL

Introduction:

Each BR Report is available in human readable form contained in a PDF file. It is also available in machine readable XBR Language contained in a XML file. Both these versions are available NSE website and also on the websites of respective participating organisations.

In this post I will mention the benefits of using the latter. As an example; I will use only energy consumption data of 3 leading Indian IT companies.

What is BRR?

In 2012, the Securities and Exchange Board of India (SEBI) mandated the top 100 listed companies by market capitalisation to file Business Responsibility Reports (SEBI-BRRs/ BRR) through the Listing Agreement. 

These disclosures were intended to enable businesses to engage more meaningfully with their stakeholders, and encourage them to go beyond regulatory financial compliance and report on their social and environmental impacts. 

The requirement for filing BRRs was extended to the top 500 listed companies by market capitalisation from the financial year 2015-16. In March 2019, the updated NVGs were released as the ‘National Guidelines for Responsible Business Conduct’ (NGRBCs).

In December 2019, SEBI extended the BRR requirement to the top 1000 listed companies by market capitalisation, from the financial year 2019-20.

BRR was changed to Business Responsibility and Sustainability Report (BRSR) with the introduction of BRSR in May 2021. Reporting is mandatory for the top 1,000 listed companies (by market capitalisation) from FY2022–23, while disclosure is voluntary for FY2021–22. Click SEBI website for more information.

What is XBRL?

XBRL (eXtensible Business Reporting Language) is a language for electronic communication of business and financial data which is revolutionising business reporting around the world. It offers major benefits to all those who have to create, transmit, use or analyse such information. XBRL has been developed by XBRL International, a not-for-profit consortium of over 600 companies and agencies which is promoting its worldwide use. Please click XBRI org for additional information.

Key benefits of XBRL and XML file format:

Automate the data capture process:

The benefit of using the machine readable XBRL  is as follows. You can automate the process of capturing the data from XBRL  from one or many XML files. And then bringing in data in to a report you want to prepare. Once you have the data you can manipulate the data. This must be the reason the report is made machine readable by regulators. Regulators can capture data from hundreds of such reports to prepare their report. 

Get the precise specific data points:

With XBRL  you can capture only the specific data points you want for further study. My example below will show how specific data points related to energy consumption were captured. 

You can manually read, copy and capture the data as well. But if you want to capture data from many files, then the process becomes tedious and prone to error. It is also difficult to estimate time to complete the manual task. 

An example:

By writing a script (a few lines of code in Python) you will be able to get the precise information you wants. You can bring that information in a report by automating this task.  

Here I have scrapped energy usage data of three leading Indian IT companies for year 2021-22. This post is for educational purpose only. 

Section - I) covers essential and leadership indicators from the BRR report. 

Section - II) covers ratios from the BRR report and prepared by me. 

These ratios can be compared across the companies. 

Ramsar Sites in India

India, on its 75th year of Independence (15th August), achieved a milestone of 75 Ramsar sites. 

It recently added 11 more wetlands to the list of Ramsar sites to make total 75 Ramsar sites covering an area of 13 lakh 26 thousand 677 Hectare in the country. 

I have created an interactive map. Kindly visit the map at https://andybandra.github.io/ramsar_india/ You can see and click the map shown below.

On the map you may click an icon to get the name and state of a site, and its area in hectares.  

India is one of the Contracting Parties to Ramsar Convention, signed in Ramsar, Iran in 1971. India signed it on 1st February 1982. These are wetlands deemed to be of "international importance" under the Ramsar Convention.

What is RAMSAR Wetland Sites

The Ramsar Convention is an international treaty for the conservation and sustainable utilization of wetlands, recognizing the fundamental ecological functions of wetlands and their economic, cultural, scientific, and recreational value.

Tamil Nadu has the highest number of Ramsar Sites in India with 14 Ramsar Sites. The largest site is marked in blue icon. It is the Sundarbans National Park a national park, tiger reserve and biosphere reserve in West Bengal,

The list is available at https://en.wikipedia.org/wiki/List_of_Ramsar_sites_in_India.

75 Ramsar India Sites

CSR-Dashboard

The Benefits of Digital Dashboards for Corporate Social Responsibility

Updated on April 3, 2024

Introduction

Corporate Social Responsibility (CSR) is a self-regulating business model that helps a company be socially accountable. In this digital age, dashboards have become a significant tool in managing CSR activities effectively. Let's delve into the benefits of digital dashboards for CSR.

Real-Time Data

Digital dashboards provide real-time updates and insights, enabling companies to make immediate decisions based on current data. This is particularly useful in CSR initiatives where timely response is crucial.

Improved Transparency

With digital dashboards, companies can share their CSR progress with stakeholders and the public in a transparent manner. This can enhance the company's reputation and build trust among its stakeholders.

Efficient Resource Allocation

Digital dashboards allow companies to see which CSR initiatives are performing well. This can help them allocate resources more efficiently, ensuring that their CSR efforts have the greatest impact.

Let's begin:

I have developed a very simple and easy to understand spend dashboard for corporate social responsibility. it is intended for senior CSR executives such as CSR committee members.

How is this dashboard organised?

On the left hand side, you have the KPIs. and on the right hand side, you have the respective spend shown in percentage of the total. In KPIs, you have the yearly spend, spend by domain (such as education), spend by location ( e.g. state), spent by NGO. It quickly gives a bird eye view of the spend. By choice, it's a static dashboard. It can be updated and customised as often as required. It can be put in conference room, in the reception area for communicating the progress of CSR spend.

Reading the dashboard:

Let's say you want to know the spend on Domain – health. It is shown as 27% as a numeral as well as a corresponding darkened arc in a circle. The arc starts from equivalent position of 9 o'clock on the clock face. Any progresses clock wise. Showing the data in percentages of the total, helps in getting a grasp of the size of the proportion. Let's take another example. We want to know the spend on the top NGO as a percentage of the total. It is shown as 35%. This will help you take an executive decision such as reducing the spend on the top NGO.

How is this dashboard made?

It is drawn using 100% Visual Basic For Applications (VBA). It is customisable in so many different ways. Sustainable Development Goals (SDGs) can also be linked. Similarly you can add photos, logos, other art clippings. 

The concept can be extended to cover other functions namely Sustainability, Marketing, Social Media, Sales, Admin. And many more.

It is not using chars from excel and pasting it in Dashboard. It uses native shape objects of PowerPoint. 

But it uses excel for data and necessary calculations. The VBA code resides in Excel. You may put your actual data. Such static visualisations have great impact in corporate conference room discussions. 

Conclusion

Digital dashboards offer numerous benefits for managing CSR initiatives. By providing real-time data, improving transparency, and aiding in resource allocation, they can help companies make a significant social impact.

Hope you like it. Please do give your suggestions.