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Observation-based data of primary and secondary organic carbon in ambient particulate matter (PM) are essential for model evaluation, climate and air quality research, health effect assessments, and mitigation policy development. Since there are no direct measurement tools available to quantify primary organic (POC) and secondary organic carbon (SOC) as separate quantities, their estimation relies on inference approaches using relevant measurable PM constituents. In this study, we measured hourly carbonaceous components and major ions in PM 2.5 for a year and a half in suburban Hong Kong from July 2020 to December 2021. We differentiated POC and SOC using a novel Bayesian inference approach. The hourly POC and SOC data allowed us to examine temporal characteristics varying from diurnal and weekly patterns to seasonal variations, as well as their evolution characteristics during individual PM 2.5 episodes. A total of 65 city-wide PM 2.5 episodes were identified throughout the entire study period, with SOC contributions during individual episodes varying from 10 % to 66 %. In summertime typhoon episodes, elevated SOC levels were observed during daytime hours, and high temperature and NOx levels were identified as significant factors contributing to episodic SOC formation. Winter haze episodes exhibited high SOC levels, likely due to persistent influences from regional transport originating from the northern region to the sampling site. Enhanced SOC formation was observed with increase in the nocturnal NO3 radical (indicated by the surrogate quantity of [ NO2 ][ O3 ]) and under conditions characterized by high water content and strong acidity. These results suggest that both NO3 chemistry and acid-catalyzed aqueous-phase reactions likely make notable contributions to SOC formation during winter haze episodes. The methodology employed in this study for estimating POC and SOC provides practical guidance for other locations with similar monitoring capabilities in place. The availability of hourly POC and SOC data is invaluable for evaluating and improving atmospheric models, as well as understanding the evolution processes of PM pollution episodes. This, in turn, leads to more accurate model predictions and a better understanding of the contributing sources and processes. [ABSTRACT FROM AUTHOR]

Building information modeling (BIM) has been leveraged to reduce manual efforts in the life cycle assessment (LCA) of buildings. However, data interoperability between BIM and LCA tools remains a significant challenge because of disparate data structures, leading to a deficiency in automatic data mapping methods. Few studies have adopted professional BIM and LCA tools to evaluate the embodied carbon of prefabricated buildings at multiple spatial levels. Thus, this paper developed a BIM-integrated LCA solution to automate the embodied carbon assessment of prefabricated buildings based on a five-level framework: material, component, assembly, flat, and building. The solution framework involved three modules: (1) BIM data preparation, (2) data extraction and integration, and (3) embodied carbon assessment. An Industry Foundation Classes (IFC)-enabled data transfer tool was developed to adapt BIM data to the LCA data structure automatically. A real-life prefabricated building in Hong Kong was used to validate the feasibility of the developed solution by comparing it with the traditional LCA method. Embodied carbon was reported in five levels. The cradle-to-end-of-construction embodied carbon of the case building was calculated as 561 kg CO 2 /m2, showing an acceptable 1% discrepancy with traditional LCA results owing to inevitable quantity differences between design and construction. The results also indicate a dramatical time reduction in the LCA modeling process from 729 min to 62 min, achieving a 91.5% efficiency improvement. It can thus practically increase practitioners' willingness to conduct LCA at an early design stage with quick feedback. The developed solution also extends the knowledge on automatic BIM-integrated LCA methodologically by addressing data interoperability using the IFC standard. Further, it provides systematic insights into the embodied carbon emissions of prefabricated buildings based on the five-level theoretical framework, guiding low-carbon designs for prefabricated buildings. • Embodied carbon assessment is automated by integrating BIM into LCA. • A tool named BIMToSimaPro is developed to automate data transfer from BIM to LCA. • Data interoperability between BIM and LCA is enhanced using the IFC standard. • A five-level framework is proposed for standardized embodied carbon evaluations. • The solution achieves consistent carbon results with a 91.5% efficiency improvement. [ABSTRACT FROM AUTHOR]