Heterogeneous N2O5 Uptake During Winter: Aircraft Measurements During the 2015 WINTER Campaign and Critical Evaluation of Current Parameterizations

Nocturnal dinitrogen pentoxide (N2O5) heterogeneous chemistry impacts regional air quality and the distribution and lifetime of tropospheric oxidants. Formed from the oxidation of nitrogen oxides, N2O5 is heterogeneously lost to aerosol with a highly variable reaction probability, γ(N2O5), dependent on aerosol composition and ambient conditions. Reaction products include soluble nitrate (HNO3 or NO3−) and nitryl chloride (ClNO2). We report the first‐ever derivations of γ(N2O5) from ambient wintertime aircraft measurements in the critically important nocturnal residual boundary layer. Box modeling of the 2015 Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign over the eastern United States derived 2,876 individual γ(N2O5) values with a median value of 0.0143 and range of 2 × 10−5 to 0.1751. WINTER γ(N2O5) values exhibited the strongest correlation with aerosol water content, but weak correlations with other variables, such as aerosol nitrate and organics, suggesting a complex, nonlinear dependence on multiple factors, or an additional dependence on a nonobserved factor. This factor may be related to aerosol phase, morphology (i.e., core shell), or mixing state, none of which are commonly measured during aircraft field studies. Despite general agreement with previous laboratory observations, comparison of WINTER data with 14 literature parameterizations (used to predict γ(N2O5) in chemical transport models) confirms that none of the current methods reproduce the full range of γ(N2O5) values. Nine reproduce the WINTER median within a factor of 2. Presented here is the first field‐based, empirical parameterization of γ(N2O5), fit to WINTER data, based on the functional form of previous parameterizations

Wintertime Spatial Distribution of Ammonia and its Emission Sources in the Great Salt Lake Region

Ammonium-containing aerosols are a major component of wintertime air pollution in many densely populated regions around the world. Especially in mountain basins, the formation of persistent cold-air pools (PCAPs) can enhance particulate matter with diameters less than 2.5 µm (PM2.5) to levels above air quality standards. Under these conditions, PM2.5 in the Great Salt Lake region of northern Utah has been shown to be primarily composed of ammonium nitrate; however, its formation processes and sources of its precursors are not fully understood. Hence, it is key to understanding the emission sources of its gas phase precursor, ammonia (NH3). To investigate the formation of ammonium nitrate, a suite of trace gases and aerosol composition were sampled from the NOAA Twin Otter aircraft during the Utah Winter Fine Particulate Study (UWFPS) in January and February 2017. NH3 was measured using a quantum cascade tunable infrared laser differential absorption spectrometer (QC-TILDAS), while aerosol composition, including particulate ammonium (pNH4), was measured with an aerosol mass spectrometer (AMS). The origin of the sampled air masses was investigated using the Stochastic Time-Inverted Lagrangian Transport (STILT) model and combined with an NH3 emission inventory to obtain model-predicted NHx (=NH3+pNH4) enhancements. Enhancements represent the increase in NH3 mixing ratios within the last 24 h due to emissions within the model footprint. Comparison of these NHx enhancements with measured NHx from the Twin Otter shows that modelled values are a factor of 1.6 to 4.4 lower for the three major valleys in the region. Among these, the underestimation is largest for Cache Valley, an area with intensive agricultural activities. We find that one explanation for the underestimation of wintertime emissions may be the seasonality factors applied to NH3 emissions from livestock. An investigation of inter-valley exchange revealed that transport of NH3 between major valleys was limited and PM2.5 in Salt Lake Valley (the most densely populated area in Utah) was not significantly impacted by NH3 from the agricultural areas in Cache Valley. We found that in Salt Lake Valley around two thirds of NHx originated within the valley, while about 30 % originated from mobile sources and 60 % from area source emissions in the region. For Cache Valley, a large fraction of NOx potentially leading to PM2.5 formation may not be locally emitted but mixed in from other counties

Limitations in representation of physical processes preven successful simulation of PM2.5 during KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol by −64 % but overestimates nitrate aerosol by 36 %. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally-produced sulfate increased from 1 % to 46 % of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements

Quantifying TOLNet Ozone Lidar Accuracy During the 2014 DISCOVER-AQ and FRAPP Campaigns

The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure high-resolution atmospheric profiles of ozone. The accurate characterization of these lidars is necessary to determine the uniformity of the network calibration. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission and the Front Range Air Pollution and Photochemistry xperiment (FRAPP) to measure ozone variations from the boundary layer to the top of the troposphere. This study presents the analysis of the intercomparison between the TROPOZ, TOPAZ, and LMOL lidars, along with comparisons between the lidars and other in situ ozone instruments including ozonesondes and a P-3B airborne chemiluminescence sensor. The TOLNet lidars measured vertical ozone structures with an accuracy generally better than 15 % within the troposphere. Larger differences occur at some individual altitudes in both the near-field and far-field range of the lidar systems, largely as expected. In terms of column average, the TOLNet lidars measured ozone with an accuracy better than 5 % for both the intercomparison between the lidars and between the lidars and other instruments. These results indicate that these three TOLNet lidars are suitable for use in air quality, satellite validation, and ozone modeling efforts

Jumping into Modeling: Elementary Mathematical Modeling with School and Community Contexts

Mathematical modeling is a high-leverage topic, critical STEM education and civic engagement. This study investigates culturally responsive, school and community-based approaches that support mathematical modeling with elementary students. Specifically, we analyzed two modeling lessons in one fifth grade classroom, with a focus on how students drew upon their experiences and funds of knowledge as they engaged in the mathematical modeling process. Our findings illustrate different ways that students' experiences and situational knowledge informed and guided their modeling activity, including the quantities that they deemed relevant, and how they interpreted and refined their solutions. We also attend to the teacher's role in supporting such connections. Implications for mathematics teacher educators and research are included. [For the complete proceedings, see ED606556.]Elementary EducationMiddle SchoolsGrade 5Intermediate Grade

Promoting Equity in Mathematics Teacher Preparation: A Framework for Advancing Teacher Learning of Children\u27s Multiple Mathematics Knowledge Bases

Research repeatedly documents that teachers are underprepared to teach mathematics effectively in diverse classrooms. A critical aspect of learning to be an effective mathematics teacher for diverse learners is developing knowledge, dispositions, and practices that support building on children\u27s mathematical thinking, as well as their cultural, linguistic, and community-based knowledge. This article presents a conjectured learning trajectory for prospective teachers\u27 (PSTs\u27) development related to integrating children\u27s multiple mathematical knowledge bases (i.e., the understandings and experiences that have the potential to shape and support children\u27s mathematics learning--including children\u27s mathematical thinking, and children\u27s cultural, home, and community-based knowledge), in mathematics instruction. Data were collected from 200 PSTs enrolled in mathematics methods courses at six United States universities. Data sources included beginning and end-of-semester surveys, interviews, and PSTs\u27 written work. Our conjectured learning trajectory can serve as a tool for mathematics teacher educators and researchers as they focus on PSTs\u27 development of equitable mathematics instruction

Transforming Mathematics Teacher Education: An Equity-Based Approach

This book builds on the Teachers Empowered to Advance Change in Mathematics (TEACH Math) project, which was an initiative that sought to develop a new generation of preK-8 mathematics teachers to connect mathematics, children’s mathematical thinking, and community and family knowledge in mathematics instruction – or what we have come to call children’s multiple mathematical knowledge bases in mathematics instruction, with an explicit focus on equity. Much of the work involved in the TEACH Math project included the development of three instructional modules for preK-8 mathematics methods courses to support the project’s goals. These activities were used and refined over eight semesters, and in Fall 2014 shared at a dissemination conference with other mathematics teacher educators from a variety of universities across the United States. Chapter contributions represent diverse program and geographical contexts and teach prospective and practicing teachers from a variety of socioeconomic and ethnic backgrounds, in particular providing accounts of supports, challenges, and tensions in implementing equity-based mathematics teacher education. The chapters supply rich evidence and illustrative examples of how other mathematics teacher educators and professional developers might make the modules work for their unique practices, courses, workshops, and prospective teachers/teachers. It promises to be an important resource for offering guidance and examples to those working with prospective teachers of mathematics who want to create positive, culturally responsive, and equity-based mathematics experiences for our nation’s youth.https://digitalcommons.tacoma.uw.edu/education_books/1022/thumbnail.jp

Prospective Teachers' Perceptions, Beliefs, and Dispostions toward Students' Family, Community, and Culture

Research has repeatedly documented that teachers are underprepared to teach mathematics effectively in diverse classrooms. We believe critical aspect of learning to be an effective mathematics teacher for diverse learners is developing knowledge, dispositions, and practices that support capitalizing on children's cultural, linguistic, and community-based knowledge and experiences in mathematics instruction. This study examined beginning perceptions, beliefs, and dispositions of prospective teachers (PSTs) toward students' family, community, and culture. Results indicate that PSTs hold a range of beliefs based on how they see the resources and supports available to students in the home and community, how they compare and contrast themselves with their students and the students with each other, and how they see the nature of the relationships that can and should be formed by teachers with students and families. [For the complete proceedings, see ED584829.]Higher Educatio

Long-term air quality trends in fast-growing future megacities in the tropics

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Learning to Leverage Children's Multiple Mathematical Knowledge Bases in Mathematics Instruction

In this article, the authors explore prospective elementary teachers' engagement with and reflection on activities they conducted to learn about a single child from their practicum classroom. Through these activities, prospective teachers learned about their child's mathematical thinking and the interests, competencies, and resources she or he brought to the mathematics classroom, and then wrote reports that included instructional suggestions as to next steps to further the child's growth in mathematics. The authors' analyses of these reports indicate that there were a variety of ways which prospective teachers made connections to one or more of their child's knowledge bases. In a high percentage of cases, prospective teachers attended to one of these knowledge bases, indicating that they were attending to particularities about their child and developing the dispositions to continue to do so. Implications for research and practice are discussed