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Science and health journalists have incorporated digital media as a source for their daily news production process, but little is known about the potential impacts of using digital media data to inform the news production process in the context of a global pandemic, where information is rapidly changing. During the COVID-19 pandemic, families have struggled to ensure economic stability and good health as well as their children’s learning and development. The Child Trends News Service sought to broaden access to science-based information to support families during the pandemic through television news, testing whether digital media can be used to understand parents’ concerns, misconceptions, and needs in real time. This article presents that digital media data can supplement traditional ways of conducting audience research and help tailor relevant content for families to garner an average of 90 million views per report. 

Abstract. Camphene, a dominant monoterpene emitted from both biogenic and pyrogenicsources, has been significantly understudied, particularly in regard tosecondary organic aerosol (SOA) formation. When camphene represents asignificant fraction of emissions, the lack of model parameterizations forcamphene can result in inadequate representation of gas-phase chemistry andunderprediction of SOA formation. In this work, the first mechanistic study of SOA formation from camphene was performed using the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A). GECKO-A was used to generate gas-phase chemical mechanisms for camphene and two well-studied monoterpenes, α-pinene and limonene, as well as to predict SOAmass formation and composition based on gas/particle partitioning theory. Themodel simulations represented observed trends in published gas-phase reactionpathways and SOA yields well under chamber-relevant photooxidation and darkozonolysis conditions. For photooxidation conditions, 70 % of thesimulated α-pinene oxidation products remained in the gas phasecompared to 50 % for limonene, supporting model predictions andobservations of limonene having higher SOA yields than α-pinene underequivalent conditions. The top 10 simulated particle-phase products in theα-pinene and limonene simulations represented 37 %–50 % ofthe SOA mass formed and 6 %–27 % of the hydrocarbon mass reacted. Tofacilitate comparison of camphene with α-pinene and limonene, modelsimulations were run under idealized atmospheric conditions, wherein thegas-phase oxidant levels were controlled, and peroxy radicals reacted equallywith HO2 and NO. Metrics for comparison included gas-phasereactivity profiles, time-evolution of SOA mass and yields, andphysicochemical property distributions of gas- and particle-phaseproducts. The controlled-reactivity simulations demonstrated that (1)in the early stages of oxidation, camphene is predicted to form very low-volatility products, lower than α-pinene and limonene, which condenseat low mass loadings; and (2) the final simulated SOA yield for camphene(46 %) was relatively high, in between α-pinene (25 %) andlimonene (74 %). A 50 % α-pinene + 50 % limonene mixture was then used as a surrogate to represent SOA formation from camphene; while simulated SOA mass and yield were well represented, the volatility distribution of the particle-phase products was not. To demonstrate the potential importance of including a parameterized representation of SOA formation by camphene in air quality models, SOA mass and yield were predicted for three wildland fire fuels based on measured monoterpene distributions and published SOA parameterizations for α-pinene and limonene. Using the 50/50 surrogate mixture to represent camphene increased predicted SOA mass by 43 %–50 % for black spruce and by 56 %–108 % for Douglas fir. This first detailed modeling study of the gas-phase oxidation of camphene and subsequent SOA formation highlights opportunities for future measurement–model comparisons and lays a foundation for developing chemical mechanisms and SOA parameterizations for camphene that are suitable for air quality modeling.