Comparison of Different Methods of Forecasting the Trend of Greenhouse Gas Emissions from Iran's Agricultural Sector

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Pezeshk Fateme; ZARE MEHRJORDI MOHAMMAD REZA; Amirtaimoori Somayeh; Mirzaei Khalilabadi Hamid Reza; Naghavi Somayeh

Educational Videos and Scientific Workshops

Scientific Information Database

ISSN: 2588-4824

Journal Paper

Paper Information

Journal: JOURNAL OF NATURAL ENVIRONMENT HAZARDS Year:2024 | Volume: | Issue: Page(s): 57-72

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

Download:

Cites:

Information Journal Paper

Title

Comparison of Different Methods of Forecasting the Trend of Greenhouse Gas Emissions from Iran's Agricultural Sector

Author(s)

Keywords

Greenhouse GasesQ4

Forecasting MethodsQ4

Agriculture IranQ4

Abstract

The emission of Greenhouse Gases is the main cause of global warming and environmental problems. The agricultural sector is one of the major sources of emissions so one-third of the greenhouse gas emissions in the world are related to agricultural systems. Today, forecasting is considered an important planning tool for policymakers. Forecasting the amount of greenhouse gas emissions can show a picture of the future for policymakers and help them in making strategic decisions. There are various methods for predicting variables. This study aims to compare the methods of forecasting and the emission trend of the most important Greenhouse Gases (methane, carbon dioxide, and nitrogen oxide) from Iran's agricultural sector. The necessary statistics and information were collected annually between 1990 and 2019 from the websites of the Food and Agriculture Organization of the United Nations, the World Bank, and the energy balance sheet of the Ministry of Energy, and to predict the variables from univariate methods of autoregressive integrated moving average (ARIMA), single exponential smoothing with trend, double exponential smoothing with trend, Holt-Winters multiplicative and Holt-Winters additive and multivariate model of vector autoregressive were used. Based on the research findings, methods of Holt-Winters additive, artificial neural network, and single exponential smoothing with trend provided the best forecast for methane gas, carbon dioxide, and nitrogen oxide, respectively. The results showed that the emission trend of methane and nitrogen oxide gases will be downward and the amount of carbon dioxide emission will be upward. The results can help predict the Greenhouse Gases released from the agricultural sector and apply appropriate policies accordingly.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops

Download

Move to top

وبگردی