Atmospheric pollution in Ulaanbaatar: Persistence and long-run trends

This paper investigates the presence of long-run trends and persistence in various pollutants in the city of Ulaanbaatar, Mongolia using fractional integration. Using daily data from January 1st, 2022 until May 31st, 2024 we investigate the statistical properties of four pollutants, namely, NO2, SO2, PM10, and PM2.5. The results indicate the presence of significant negative time trends in the cases of SO2 and PM2.5 and evidence of long memory and mean reverting patterns in all four pollutants. Policy implications of the results obtained are reported at the end of the paper.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-06-03
DOI
https://doi.org/10.1371/journal.pone.0322991
Citations
2
Primary Topic
Water Resources and Management
Type
article
Field-Weighted Citation Impact
3.43

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Atmospheric pollution in Ulaanbaatar: Persistence and long-run trends

Chultem Batbold, Luis A. Gil-Alaña, Сономдагва Чонохуу, Ariundelger Ariunsaikhan
2 citations
PLoS ONE
Water Resources and Management
3.43
article

Atmospheric pollution in Ulaanbaatar: Persistence and long-run trends

Chultem Batbold, Luis A. Gil-Alaña, Сономдагва Чонохуу, Ariundelger Ariunsaikhan
article en
2 citations

Abstract

This paper investigates the presence of long-run trends and persistence in various pollutants in the city of Ulaanbaatar, Mongolia using fractional integration. Using daily data from January 1st, 2022 until May 31st, 2024 we investigate the statistical properties of four pollutants, namely, NO2, SO2, PM10, and PM2.5. The results indicate the presence of significant negative time trends in the cases of SO2 and PM2.5 and evidence of long memory and mean reverting patterns in all four pollutants. Policy implications of the results obtained are reported at the end of the paper.

PLoS ONEVol. 20(6)
Universidad Francisco de Vitoria (ES), University of Łódź (PL), Społeczna Akademia Nauk (PL), National University of Mongolia (MN), Universidad de Navarra (ES)
Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España
Openalex Percentile: Top 9%
Water Resources and Management
3.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.