Air pollution is becoming a prominent social problem in fast-growing Asian economies. Taking the Bangkok Metropolitan Region (BMR) as a case, we conducted an observational study of fine particulate matter (PM_2.5) and acid deposition, consisting of their continuous monitoring at two sites. To find the major contributing sources of PM_2.5, the PM composition data were analyzed by a receptor modeling approach while the pollution load from BMR sources to the air was characterized by an emission inventory. Our data show generally alarming levels of PM_2.5 in the region, of which transportation and biomass burning are two major sources. In this paper, we present a general overview of our observational findings, contrast the scientific information with the policy context of air quality management in BMR, and discuss policy implications. In BMR, where a set of conventional regulatory instruments on air quality management are already in place, a solution for the air pollution problem should lie in a combination of air quality regulation and other policies, such as energy and agricultural policies.

Pollution of rivers is a challenge for many countries. In the Citarum watershed, Indonesia, where pollution has been an emerging issue nationwide, many programs and policies have been set up. However, implementation of all the planned programs and the significance of their contributions toward water quality improvement of the Citarum River have not been analyzed. In this paper, we present original research on evaluating water quality programs planned to achieve outputs by using uncertainty and sensitivity analysis for a river. The essential inputs included: (1) key parameters, (2) priority planned programs, and (3) interrelationships between programs, parameters, and the level of successfulness of water quality control programs. The first and second inputs were prepared simultaneously using Principal Component Analysis (PCA) and Analytical Hierarchy Process (AHP). The latter was obtained using the Delphi method to obtain the related stakeholders’ opinions. Finally, we explore Monte Carlo simulation to analyze parameter uncertainty and sensitivity contributing to the program’s effectiveness. By implementing all the water quality control programs, the results showed that cadmium, BOD, and fecal coliform were the most affected parameters. In addition, the most effective programs to improve the pollution index were domestic waste, farming, solid waste, and water resource programs. If those programs were implemented collectively, the probability of reducing the pollution index was within a range 2.01–36.22% from the base case.

Quantifying the co-benefits of renewable energy investments can aid policymakers in identifying technologies capable of generating significant social, economic, and environmental benefits to effectively offset mitigation costs. Although there has been a growing body of work evaluating co-benefits, few studies have compared the potential co-benefits of several technologies across different regions in key countries. This study fills this gap by formulating a new modeling structure to assess the environmental–health–economic co-benefits of hybrid renewable energy systems (HRESs) in different parts of Indonesia. The proposed model is unique in that it incorporates various techno-economic activities to assess air quality, health, and economic benefits and then presents results as part of a cost–benefit analysis. From the intervention scenario, the modeling results show that installing 0.5 GW grid-connected solar PV, 100 MW of wind turbines, and a 100 MW biomass generator to cover a total of 1.64 million residential load units in the Bali province can avoid GHGs, PM_2.5, disability-adjusted life years (DALYs), and provide health savings of 1.73 Mt/y, 289.02 t/y, 1648, and 6.16 million USD/y, respectively. In addition, it shows that the payback period is enhanced by one year, while the net present value is increased by 28%. In Jakarta, a 3 GW solar PV plant and a 100 MW biomass generator that supply 5.8 million residential load units can deliver 32,490 averted DALYs and 652.81 million USD/y of health care savings. Nationally, the contribution of renewable energy to the electricity supply mix could grow from the 2020 baseline of 18.85% to 26.93%, reducing dependence on oil and coal contribution by 5.32%.

The application of chromium sulfate in tanning operations yields chromium-laden wastewater, posing significant environmental risks. This research explores electrocoagulation as a remedial measure for tannery effluents. Varied parameters—pH (4, 7, 10), electric currents (0.5, 1.0, 1.5 A), and...

Emission inventory (EI) data are crucial to provide source apportionment and relative strength of various air pollutant sources in a city. The process of EI compilation can be either bottom-up or top-down, which depends on data availability and other resources. For a city like Bogor, known as a buffer zone of the capital of the Republic of Indonesia, these EI data are now available only for greenhouse gases (GHGs) but not for the air pollutants. Therefore, a top-down EI was designed and implemented for the city in the base year of 2016. Note that the sources of activity data were compiled from the previously arranged GHGs EI database as well as some other data gathered from the local authority. We adopted the EI framework of the Atmospheric Brown Cloud Emission Inventory Manual spreadsheet for the compilation. We included SO2, CO, NO2, PM10, PM2.5, NMVOC, and PM components (black carbon and organic carbon). Point sources, area sources, as well as mobile sources, were considered in the emission estimation. The latter species were included as they are known as strong short-lived climate-forcing pollutants (SLCPs). On-road transport contributed significantly to SO2, NMVOC, and PM2.5, with a portion of 60-86% of the total emission. Industrial combustion sources dominated the shares to the total emissions of NOx (91%) and CO (92%). Based on this baseline information, we then proposed the source wise clean air action plan for the city in order to reduce the emission. A more accurate and up to date EI database should be done through a survey to get local representative activity data and to be compiled on a regular basis.