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PM2.5 Temporal Pattern in Jambi City: Meteorological Drivers and Air Mass Trajectory Analysis Benedy Fajar; Muhammad Damris; Kemas Rahmat Saleh Wiharja; Elma Mutmainnah; Noorlin Mohamad; Rizki Andre Handika
Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Vol 23, No 2 (2026): July 2026
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/presipitasi.v23i2.402-413

Abstract

Air pollution, particularly particles with a diameter of less or equal than 2.5 micrometers (PM2.5), has become an important global health and environmental problem. Jambi City in Sumatra is highly susceptible to this issue, both locally and particularly influenced by forest fires. As early studies were conducted over a short period, this study examined the meteorological factors that influenced PM2.5 levels and estimated the pollutant transport pathways over two years in the post-COVID-19 period (2023-2024). The methods employed were time-series analysis, scatter-plot evaluation, multiple linear regression analysis, and backward trajectory modeling using HYSPLIT. The results show that the average PM2.5 concentration in 2023 (30.53 µg/m³) was higher than in 2024 (25.36 µg/m³), with night-time levels generally exceeding day-time levels. 3.69% of the days exceeded Indonesia’s daily air quality standard, while 90.83% surpassed the stricter WHO guideline. Meteorological factors explained only 23–38% of PM2.5, with temperature positively correlated, wind speed showing mixed effects, and humidity and rainfall negatively correlated.. The major PM₂.₅ sources influenced by the southeast–South Sumatra, particularly South Sumatra, highlighting the strong stimulus of transboundary emissions alongside local sources. In the future, studies focusing on chemistry-based source apportionment are needed to accurately separate each contributing source.
Analysis of the Effect of Wastewater Quality on the Effectiveness of Eco-Enzyme Hariestya Viareco; Shally Yanova; Jalius Jalius; Muhammad Naswir; Nabila Sastra Dewi; Elma Mutmainnah; Besse Syaharani Ziadah; Muhammad Khatamsi; Prameswari Amalia Putri; Kintan Larasati Zahra; Dini Sri Wahyuni; Harry Fajra Meduripa; Jumary Iskandar
Journal of Community Based Environmental Engineering and Management Vol. 9 No. 1 (2025): March 2025
Publisher : Department of Environmental Engineering - Universitas Pasundan - Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jcbeem.v9i1.20142

Abstract

Eco-enzyme represents a biological solution derived from the fermentation of organic materials, evaluated for its effectiveness in industrial wastewater treatment. This study examines  to investigate the effectiveness of eco-enzymes in improving the quality of industrial wastewater by analyzing their impact on four specific types of liquid waste: landfill leachate, tofu wastewater, batik wastewater, and laundry wastewater. Samples were treated with eco-enzyme at specific concentrations and incubated for 5 days, followed by chemical analysis. Eco-enzyme reduced ammonia levels in landfill leachate by 57% to 8.83 mg/L, though COD and BOD values rose to 18,114.6 mg/L and 46,709 mg/L, respectively, exceeding effluent standards. In tofu wastewater, COD and BOD decreased by 72% and 75% to 4,189.68 mg/L and 2,395.3 mg/L, respectively, but remained above regulatory limits. Batik wastewater showed increases in most parameters, with COD and BOD reaching 6,838.85 mg/L and 3,193.5 mg/L. For laundry wastewater, surfactants decreased by 55% to 12.97 mg/L, but BOD and TSS increased. These findings indicate that while eco-enzyme can reduce specific pollutants like ammonia and surfactants, its application can also elevate COD and BOD levels in some cases. Additional treatment processes, such as aeration or coagulation, are required to achieve effluent standards. Despite its limitations, eco-enzyme holds potential as an environmentally friendly option for industrial wastewater management when integrated with complementary technologies.