Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) concentrations in a Small Industrial Bakery Using ARIMA

Gbadebo İsmaila Olatona; Sherifdeen Mosebolatan Oyedokun; Shuaib Adisa

doi:10.34110/forecasting.1807051

Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) concentrations in a Small Industrial Bakery Using ARIMA

Abstract

This study investigates short-term forecasting of indoor air quality in a small industrial environment, using a bakery as a case study. An AutoRegressive Integrated Moving Average (ARIMA) (5,1,0) model was applied to predict variations in carbon dioxide (CO₂) concentrations, a key proxy indicator for ventilation efficiency and occupational exposure, which was monitored over 57 days and modelled to capture short-term fluctuations. The model effectively captured temporal dependencies, with significant autoregressive terms (p < 0.05) highlighting the influence of past values on short-term forecasts. However, substantial unexplained variability was observed, suggesting that external drivers such as ventilation, operational schedules, and equipment use play a critical role in shaping indoor air quality. Although ARIMA is a well-established forecasting method, this study demonstrates its value as a low-cost, data-efficient tool for small industries in resource-limited settings where complex monitoring systems and large datasets may be unavailable. By forecasting CO₂ dynamics, facility operators can anticipate periods of elevated indoor exposure and adjust ventilation strategies to mitigate risks, thereby supporting worker health, safety, and productivity. The findings provide a proof-of-concept for integrating classical time-series forecasting into occupational environmental management. However, future research should extend this approach to multivariate or hybrid ARIMA–machine learning models, incorporate additional pollutants with direct public health implications e.g., PMs, NO₂, temperature, and relative humidity, then validate across multiple industrial contexts. This would enhance generalizability and strengthen the role of forecasting tools in informing ventilation policy, exposure mitigation, and regulatory compliance in small-scale industrial environments.

Keywords

References

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Details

Primary Language

English

Subjects

Applied Statistics

Journal Section

Research Article

Authors

Gbadebo İsmaila Olatona
0000-0001-9415-6265
Nigeria

Sherifdeen Mosebolatan Oyedokun
0000-0001-9013-5512
Nigeria

Shuaib Adisa ^*
0000-0001-9389-1874
Nigeria

Publication Date

March 12, 2026

Submission Date

October 20, 2025

Acceptance Date

January 5, 2026

Published in Issue

Year 2026 Volume: 10 Number: 1

DOI

https://doi.org/10.34110/forecasting.1807051

IZ

https://izlik.org/JA85CJ46MH

Cite

RIS / Bibtex

APA

Olatona, G. İ., Oyedokun, S. M., & Adisa, S. (2026). Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) concentrations in a Small Industrial Bakery Using ARIMA. Turkish Journal of Forecasting, 10(1), 62-68. https://doi.org/10.34110/forecasting.1807051

AMA

1.Olatona Gİ, Oyedokun SM, Adisa S. Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) concentrations in a Small Industrial Bakery Using ARIMA. TJF. 2026;10(1):62-68. doi:10.34110/forecasting.1807051

Chicago

Olatona, Gbadebo İsmaila, Sherifdeen Mosebolatan Oyedokun, and Shuaib Adisa. 2026. “Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) Concentrations in a Small Industrial Bakery Using ARIMA”. Turkish Journal of Forecasting 10 (1): 62-68. https://doi.org/10.34110/forecasting.1807051.

EndNote

Olatona Gİ, Oyedokun SM, Adisa S (March 1, 2026) Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) concentrations in a Small Industrial Bakery Using ARIMA. Turkish Journal of Forecasting 10 1 62–68.

IEEE

[1]G. İ. Olatona, S. M. Oyedokun, and S. Adisa, “Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) concentrations in a Small Industrial Bakery Using ARIMA”, TJF, vol. 10, no. 1, pp. 62–68, Mar. 2026, doi: 10.34110/forecasting.1807051.

ISNAD

Olatona, Gbadebo İsmaila - Oyedokun, Sherifdeen Mosebolatan - Adisa, Shuaib. “Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) Concentrations in a Small Industrial Bakery Using ARIMA”. Turkish Journal of Forecasting 10/1 (March 1, 2026): 62-68. https://doi.org/10.34110/forecasting.1807051.

JAMA

1.Olatona Gİ, Oyedokun SM, Adisa S. Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) concentrations in a Small Industrial Bakery Using ARIMA. TJF. 2026;10:62–68.

MLA

Olatona, Gbadebo İsmaila, et al. “Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) Concentrations in a Small Industrial Bakery Using ARIMA”. Turkish Journal of Forecasting, vol. 10, no. 1, Mar. 2026, pp. 62-68, doi:10.34110/forecasting.1807051.

Vancouver

1.Gbadebo İsmaila Olatona, Sherifdeen Mosebolatan Oyedokun, Shuaib Adisa. Proof-of-Concept Forecasting of Indoor Carbon Dioxide (〖CO〗_2) concentrations in a Small Industrial Bakery Using ARIMA. TJF. 2026 Mar. 1;10(1):62-8. doi:10.34110/forecasting.1807051