ArticleScientific reports2023
An integrated analysis of air pollution and meteorological conditions in Jakarta.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
The trial behind it
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Who cites it
4 citing papers in PubMed, 44 citations in OpenAlex.
- Numerical Simulation of Atmospheric Pollutant Dispersion on Campus: Impacts of Wind Environment and Newly Constructed Buildings' Height.Journal of xenobiotics · 2026Article
- Integrated analysis of meteorological conditions and agricultural yields in Indonesia using causal learning and intelligent clustering for climate change mitigation.Scientific reports · 2026Article
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Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Air pollution and climate change are general problems for society. This paper proposes an integrated analysis of the Air Quality Index (AQI) and meteorological conditions in Jakarta. The column-based data integration model is applied to create integrated data of the Air Quality Index and meteorological conditions. The integrated data is then used to generate a causal graph using the PC algorithm. The causal graph reveals that there exist causal relationships between pollutants and meteorological conditions, e.g, humidity, rainfall, wind speed, and duration of sunshine affect particulate matter 10 (PM[Formula: see text]); wind speed affects sulfur dioxide (SO[Formula: see text]); temperature affects ozone (O[Formula: see text]). The historical data records that the average wind speed is decreased and the number of unhealthy days has risen. Ozone and particulate matter are two pollutants that mainly influence poor air quality in Jakarta. The integrated data is also used to train Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) for forecasting. Experimental results show that LSTM using integrated data produces smaller errors for forecasting AQI and meteorological conditions.
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Registered trials
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.