No abstract

No abstract

This article quantifies the environmental, health, and economic co-benefits from the use of solar electricity and heat generation in the Ger area (a sub-district of traditional residences and private houses) in Ulaanbaatar (UB), Mongolia. The quantification of the featured co-benefits is based on calculating emissions reductions from the installation of the solar photovoltaic (PV) and solar water heaters. A user-friendly spreadsheet tool is developed to shed much-needed light on the steps involved in estimating these co-benefits. The tool simulates the hourly electricity and thermal energy generation, taking into account local meteorological conditions, local geographical data, and technical specifications of the solar power and heat generation systems. The tool is then employed to evaluate two intervention scenarios: (1) Installing 100 MW solar electricity, including both rooftop PV and community grids, to reduce the peak-load burden on the grid; (2) Providing solar thermal heaters for 20,000 households to replace the heating load demand from the existing heat only boilers (HOBs) in UB. The modelling results reveal a significant reduction in GHG emissions and fine particulate matter (PM2.5) (PM that is 2.5 microns or less in diameter) by 311,000 tons and 767 tons, respectively, as well as nearly 6500 disability-adjusted life years (DALYs) and an annual saving of USD 7.7 million for the local economy. The article concludes that the mainstreaming spreadsheet-based estimation tools like the one used in this article into decision-making processes can fill important research gaps (e.g., usability of assessment tools) and help translate co-benefits analyses into action in Mongolia and beyond.

In this paper, a comprehensive life-cycle assessment (LCA) is carried out in order to evaluate the multiple environmental-health impacts of the biological wastewater treatment of the fish-processing industry throughout its life cycle. To this aim, the life-cycle impact assessment method based on endpoint modeling (LIME) was considered as the main LCA model. The proposed methodology is based on an endpoint modeling framework that uses the conjoint analysis to calculate damage factors for human health, social assets, biodiversity, and primary production, based on Indonesia’s local data inventory. A quantitative microbial risk assessment (QMRA) is integrated with the LIME modeling framework to evaluate the damage on human health caused by five major biological treatment technologies, including chemical-enhanced primary clarification (CEPC), aerobic-activated sludge (AS), up-flow anaerobic sludge blanket (UASB), ultrafiltration (UF) and reverse osmosis (RO) in this industry. Finally, a life-cycle costing (LCC) is carried out, considering all the costs incurred during the lifetime. The LCA results revealed that air pollution and gaseous emissions from electricity consumption have the most significant environmental impacts in all scenarios and all categories. The combined utilization of the UF and RO technologies in the secondary and tertiary treatment processes reduces the health damage caused by microbial diseases, which contributes significantly to reducing overall environmental damage.

No abstract