Monitoring Particulate Matter with Wearable Sensors and the Influence on Student Environmental Attitudes.

The mobile monitoring of air pollution is a growing field, prospectively filling in spatial gaps while personalizing air-quality-based risk assessment. We developed wearable sensors to record particulate matter (PM), and through a community science approach, students of partnering Chicago high schools monitored PM concentrations during their commutes over a five- and thirteen-day period. Our main objective was to investigate how mobile monitoring influenced students' environmental attitudes and we did this by having the students explore the relationship between PM concentrations and urban vegetation. Urban vegetation was approximated with a normalized difference vegetation index (NDVI) using Landsat 8 satellite imagery. While the linear regression for one partner school indicated a negative correlation between PM and vegetation, the other indicated a positive correlation, contrary to our expectations. Survey responses were scored on the basis of their environmental affinity and knowledge. There were no significant differences between cumulative pre- and post-experiment survey responses at Josephinum Academy, and only one weakly significant difference in survey results at DePaul Prep in the Knowledge category. However, changes within certain attitudinal subscales may possibly suggest that students were inclined to practice more sustainable behaviors, but perhaps lacked the resources to do so.

Increasing leaf temperature reduces the suppression of isoprene emission by elevated CO2 concentration.

Including algorithms to account for the suppression of isoprene emission by elevated CO2 concentration affects estimates of global isoprene emission for future climate change scenarios. In this study, leaf-level measurements of isoprene emission were made to determine the short-term interactive effect of leaf temperature and CO2 concentration. For both greenhouse plants and plants grown under field conditions, the suppression of isoprene emission was reduced by increasing leaf temperature. For each of the four different tree species investigated, aspen (Populus tremuloides Michx.), cottonwood (Populus deltoides W. Bartram ex Marshall), red oak (Quercus rubra L.), and tundra dwarf willow (Salix pulchra Cham.), the suppression of isoprene by elevated CO2 was eliminated at increased temperature, and the maximum temperature where suppression was observed ranged from 25 to 35°C. Hypotheses proposed to explain the short-term suppression of isoprene emission by increased CO2 concentration were tested against this observation. Hypotheses related to cofactors in the methylerythritol phosphate (MEP) pathway were consistent with reduced suppression at elevated leaf temperature. Also, reduced solubility of CO2 with increased temperature can explain the reduced suppression for the phosphoenolpyruvate (PEP) carboxylase competition hypothesis. Some global models of isoprene emission include the short-term suppression effect, and should be modified to include the observed interaction. If these results are consistent at longer timescales, there are implications for predicting future global isoprene emission budgets and the reduced suppression at increased temperature could explain some of the variable responses observed in long-term CO2 exposure experiments.

Processing arctic eddy-flux data using a simple carbon-exchange model embedded in the ensemble Kalman filter.

Continuous time-series estimates of net ecosystem carbon exchange (NEE) are routinely made using eddy covariance techniques. Identifying and compensating for errors in the NEE time series can be automated using a signal processing filter like the ensemble Kalman filter (EnKF). The EnKF compares each measurement in the time series to a model prediction and updates the NEE estimate by weighting the measurement and model prediction relative to a specified measurement error estimate and an estimate of the model-prediction error that is continuously updated based on model predictions of earlier measurements in the time series. Because of the covariance among model variables, the EnKF can also update estimates of variables for which there is no direct measurement. The resulting estimates evolve through time, enabling the EnKF to be used to estimate dynamic variables like changes in leaf phenology. The evolving estimates can also serve as a means to test the embedded model and reconcile persistent deviations between observations and model predictions. We embedded a simple arctic NEE model into the EnKF and filtered data from an eddy covariance tower located in tussock tundra on the northern foothills of the Brooks Range in northern Alaska, USA. The model predicts NEE based only on leaf area, irradiance, and temperature and has been well corroborated for all the major vegetation types in the Low Arctic using chamber-based data. This is the first application of the model to eddy covariance data. We modified the EnKF by adding an adaptive noise estimator that provides a feedback between persistent model data deviations and the noise added to the ensemble of Monte Carlo simulations in the EnKF. We also ran the EnKF with both a specified leaf-area trajectory and with the EnKF sequentially recalibrating leaf-area estimates to compensate for persistent model-data deviations. When used together, adaptive noise estimation and sequential recalibration substantially improved filter performance, but it did not improve performance when used individually. The EnKF estimates of leaf area followed the expected springtime canopy phenology. However, there were also diel fluctuations in the leaf-area estimates; these are a clear indication of a model deficiency possibly related to vapor pressure effects on canopy conductance.

The effect of elevated CO2, soil and atmospheric water deficit and seasonal phenology on leaf and ecosystem isoprene emission.

Two cottonwood plantations were grown at different CO2 concentrations at the Biosphere 2 Laboratory in Arizona to investigate the response of isoprene emission to elevated [CO2] and its interaction with water deficits. We focused on responses due to seasonal variation and variation in the mean climate from one year to the next. In fall and in spring, isoprene emission rate showed a similar inhibition by elevated [CO2], despite an 8-10°C seasonal difference in mean air temperature. The overall response of isoprene emission to drought was also similar for observations conducted during the spring or fall, and during the fall of two different years with an approximate 5°C difference in mean air temperature. In general, leaf-level isoprene emission rates, measured at constant temperature and photon-flux density, decreased slightly, or remained constant during drought, whereas ecosystem-level isoprene emission rates increased. The uncoupling of ecosystem- and leaf-scale responses is not due to differential dependence on leaf area index (LAI) as LAI increased only slightly, or decreased, during the drought treatments at the same time that ecosystem isoprene emission rate increased greatly. Nor does the difference in isoprene emission rate between leaves and ecosystems appear to be due solely to increases in canopy surface temperature during the drought, though some increase in temperature was observed. It is possible that still further factors, such as increased penetration of PPFD into the canopy as a result of changes in leaf angle, reduced sink strength of the soil for atmospheric isoprene, and decreases in the mean Ci of leaves, combined with the small increases in canopy surface temperature, increased the ecosystem isoprene emission rate. Whatever the causes of the differences in the leaf and ecosystem responses, we conclude that the overall shape of the leaf and ecosystem responses to drought was constant irrespective of season or year.

Increased CO2 uncouples growth from isoprene emission in an agriforest ecosystem.

The emission of isoprene from the leaves of forest trees is a fundamental component of biosphere-atmosphere interactions, controlling many aspects of photochemistry in the lower atmosphere. As almost all commercial agriforest species emit high levels of isoprene, proliferation of agriforest plantations has significant potential to increase regional ozone pollution and enhance the lifetime of methane, an important determinant of global climate. Here we show that growth of an intact Populus deltoides plantation under increased CO2 (800 micromol x mol(-1) and 1,200 micromol x mol(-1)) reduced ecosystem isoprene production by 21% and 41%, while above-ground biomass accumulation was enhanced by 60% and 82%, respectively. Exposure to increased CO2 significantly reduced the cellular content of dimethylallyl diphosphate, the substrate for isoprene synthesis, in both leaves and leaf protoplasts. We identify intracellular metabolic competition for phosphoenolpyruvate as a possible control point in explaining the suppression of isoprene emission under increased CO2. Our results highlight the potential for uncoupling isoprene emission from biomass accumulation in an agriforest species, and show that negative air-quality effects of proliferating agriforests may be offset by increases in CO2.