Evidence map›Paper›PMID 32944863›Full record

ArticleEnvironmental science and pollution research international2021

Does the prevailing Indian agricultural ecosystem cause carbon dioxide emission? A consent towards risk reduction.

Basit Ali, Arif Ullah, Dilawar Khan

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Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Basit AliDepartment of Economics, Kohat University of Science & Technology, Kohat, Khyber Pakhtunkhwa, 26000, Pakistan.
Arif UllahDepartment of Economics, Kohat University of Science & Technology, Kohat, Khyber Pakhtunkhwa, 26000, Pakistan.
Dilawar KhanDepartment of Economics, Kohat University of Science & Technology, Kohat, Khyber Pakhtunkhwa, 26000, Pakistan. dilawarmkd@yahoo.com.ORCID http://orcid.org/0000-0001-5872-267X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, due to the increasing concentration of carbon dioxide emissions in the atmosphere, the global environment has changed dramatically. As a result, climate change, global warming, and environmental degradation-like issues have been raised. Presumably, human beings, as well as the agricultural ecosystem, become most vulnerable to these issues. In this context, the study focuses on the nexus between Indian's agricultural ecosystem and carbon dioxide emission. For the purpose of this study, annual time series data over the time span from 1990 to 2014 was used. The modern techniques, for instance, Johansen, ARDL, and Granger causality, were employed. The Johansen test and ARDL model suggest that carbon dioxide emissions and agricultural ecosystems are co-integrated. In the short run, the ARDL model suggests that a 1% increase in biomass-burned crop residues, total pesticides, and stock of livestock would increase carbon dioxide emissions by 0.26, 0.3, and 6.58% respectively. The residual diagnostics tests suggest that the ARDL model is stable, reliable, and credible in the present form. The results of the granger causality show that a unidirectional causality was found between carbon dioxide and total heads of livestock, all animal manure applied to the soil, agricultural technology, and total pesticide used in the agricultural sector. In contrast, bidirectional causality was found between the production of biomass-burned crop residues and carbon dioxide emission. Therefore, it is suggested that the government should take preemptive action to reduce the risk of environmental pollution and degradation through synchronized strategies particularly by reducing the amount of biomass-burned crop residues and usage of total pesticides in the country.

Indexed as

Carbon DioxideEcosystemAgricultureAnimalsEconomic DevelopmentHumansInformed ConsentRisk Reduction BehaviorCarbon DioxideAgricultural ecosystemARDL modelEnvironmental degradationJohansen testRisk reduction

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.