(1) Background: This study aimed to quantify the health and economic impacts of air pollution in Jakarta Province, the capital of Indonesia. (2) Methods: We quantified the health and economic burden of fine particulate matter (PM2.5) and ground-level Ozone (O3), which exceeds the local and global ambient air quality standards. We selected health outcomes which include adverse health outcomes in children, all-cause mortality, and daily hospitalizations. We used comparative risk assessment methods to estimate health burdens attributable to PM2.5 and O3, linking the local population and selected health outcomes data with relative risks from the literature. The economic burdens were calculated using cost-of-illness and the value of the statistical life-year approach. (3) Results: Our results suggest over 7000 adverse health outcomes in children, over 10,000 deaths, and over 5000 hospitalizations that can be attributed to air pollution each year in Jakarta. The annual total cost of the health impact of air pollution reached approximately USD 2943.42 million. (4) Conclusions: By using local data to quantify and assess the health and economic impacts of air pollution in Jakarta, our study provides timely evidence needed to prioritize clean air actions to be taken to promote the public’s health.

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Abstract. People living near busy roads are potentially exposed to trafficinduced air pollutants. The pollutants may intrude into the indoor environment, causing health risks to the occupants. Prediction of pollutant exposure therefore is of great importance for impact assessment and policy making related to environmentally sustainable transport. This study involved the selection of spatial interpolation methods that can be used for prediction of indoor air quality based on outdoor pollutant mapping without indoor measurement data. The research was undertaken in the densely populated area of Karees, Bandung, Indonesia. The air pollutant NO 2 was monitored in this area as a preliminary study. Nitrogen dioxide concentrations were measured by passive diffusion tube. Outdoor NO 2 concentrations were measured at 94 locations, consisting of 30 roadside and 64 outdoor locations. Residential indoor NO 2 concentrations were measured at 64 locations. To obtain a spatially continuous air quality map, the spatial interpolation methods of inverse distance weighting (IDW) and Kriging were applied. Selection of interpolation method was done based on the smallest root mean square error (RMSE) and standard deviation (SD). The most appropriate interpolation method for outdoor NO 2 concentration mapping was Kriging with an SD value of 5.45 µg/m 3 and an RMSE value of 5.45 µg/m 3 , while for indoor NO 2 concentration mapping the IDW was best fitted with an RMSE value of 5.92 µg/m 3 and an SD value of 5.92 µg/m 3 .