Bokashi fermentation of brewery's spent grains positively affects larval performance of the black soldier fly Hermetia illucens while reducing gaseous nitrogen losses.

Digestion of waste feedstocks by larvae of the black soldier fly Hermetia illucens (Diptera: Stratiomyidae) (BSF) results in proteins for animal feed and organic fertilizer with a reduced environmental footprint, but it can still have negative environmental effects through greenhouse gas (GHG) and ammonia (NH3) emissions. Both biomass conversion by BSF larvae and associated GHG and NH3 emissions can depend on substrate properties that may be optimized through microbial inoculation pre-treatments, such as bokashi fermentation. Here, we quantified the effects of bokashi fermentation of brewery's spent grains on BSF rearing metrics and associated GHG and NH3 emissions at benchtop scale. We found that bokashi fermentation increased larval biomass by 40% and shortened development time by over two days on average, compared with unfermented spent grains. In line with increased larval growth, CO2 emissions in BSF larvae treatments were 31.0 and 79.0% higher in the bokashi fermented spent grains and Gainesville substrates, respectively, compared to the unfermented spent grains. Adding BSF larvae to the spent grains increased cumulative N2O emissions up to 64.0 mg N2O kg substratedry-1 but there were essentially no N2O emissions when larvae were added to fermented spent grains. Bokashi fermentation also reduced NH3 fluxes from the volatilization of substrate nitrogen in the BSF larvae treatment by 83.7-85.8% during days 7 and 9, possibly by increasing N assimilation by larvae or by reducing the transformation of substrate NH4+ to NH3. Therefore, bokashi fermentation may be applied to improve performance of BSF larvae on a common industrial waste stream and reduce associated emissions.

Estimating inputs for dispersion modeling in mobile platform applications.

Mobile monitoring platforms (MMP) are popular in air quality studies. One application of MMP is in estimating pollutant emissions from area sources. The MMP is used to measure concentrations of the relevant species at several locations around the area source, while the associated meteorological information is measured at the same time. Emissions from the area source are inferred by fitting the measured concentrations to estimates from dispersion models. These models require meteorological inputs, such as the kinematic heat flux and the surface friction velocity, that are best computed with measurements of time resolved velocity and temperature made with 3-D sonic anemometers. Because the setting up and dismantling of a 3-D sonic anemometer is not compatible with the necessary mobility of the MMP, it is useful to use alternative instrumentation and methods that provide accurate estimates of these inputs. In this study, we demonstrate such a method based on measurements of horizontal wind speed and temperature fluctuations at a single height. The method was evaluated by comparing methane emissions from a dairy manure lagoon inferred from a dispersion model that uses modeled meteorological inputs to those inferred from measurements with 3-D sonic anemometers. The emission estimates from the modeled meteorological inputs were close to those based on measurements made with 3-D sonic anemometers. We then demonstrate how this approach can be adapted for mobile platform applications by showing that winds measured using a 2-D sonic anemometer and temperature fluctuations measured with a bead thermistor, which can all be carried or mounted on a MMP, yields results that are close to those from a 3-D sonic anemometer.

Artificial Intelligence Approach for Estimating Dairy Methane Emissions.

California's dairy sector accounts for ∼50% of anthropogenic CH4 emissions in the state's greenhouse gas (GHG) emission inventory. Although California dairy facilities' location and herd size vary over time, atmospheric inverse modeling studies rely on decade-old facility-scale geospatial information. For the first time, we apply artificial intelligence (AI) to aerial imagery to estimate dairy CH4 emissions from California's San Joaquin Valley (SJV), a region with ∼90% of the state's dairy population. Using an AI method, we process 316,882 images to estimate the facility-scale herd size across the SJV. The AI approach predicts herd size that strongly (>95%) correlates with that made by human visual inspection, providing a low-cost alternative to the labor-intensive inventory development process. We estimate SJV's dairy enteric and manure CH4 emissions for 2018 to be 496-763 Gg/yr (mean = 624; 95% confidence) using the predicted herd size. We also apply our AI approach to estimate CH4 emission reduction from anaerobic digester deployment. We identify 162 large (90th percentile) farms and estimate a CH4 reduction potential of 83 Gg CH4/yr for these large facilities from anaerobic digester adoption. The results indicate that our AI approach can be applied to characterize the manure system (e.g., use of an anaerobic lagoon) and estimate GHG emissions for other sectors.

Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

Coupled Air Quality and Boundary-Layer Meteorology in Western U.S. Basins during Winter: Design and Rationale for a Comprehensive Study.

Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical-meteorological interactions that drive high pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in Western U.S. basins. Approximately 120 people participated, representing 50 institutions and 5 countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary-layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological-chemical linkages outlined here, nor to validate complex processes within coupled atmosphere-chemistry models.

Characterizing the Performance of a Compact BTEX GC-PID for Near-Real Time Analysis and Field Deployment.

In this study, we test the performance of a compact gas chromatograph with photoionization detector (GC-PID) and optimize the configuration to detect ambient (sub-ppb) levels of benzene, toluene, ethylbenzene, and xylene isomers (BTEX). The GC-PID system was designed to serve as a relatively inexpensive (~10 k USD) and field-deployable air toxic screening tool alternative to conventional benchtop GCs. The instrument uses ambient air as a carrier gas and consists of a Tenax-GR sorbent-based preconcentrator, a gas sample valve, two capillary columns, and a photoionization detector (PID) with a small footprint and low power requirement. The performance of the GC-PID has been evaluated in terms of system linearity and sensitivity in field conditions. The BTEX-GC system demonstrated the capacity to detect BTEX at levels as high as 500 ppb with a linear calibration range of 0-100 ppb. A detection limit lower than 1 ppb was found for all BTEX compounds with a sampling volume of 1 L. No significant drift in the instrument was observed. A time-varying calibration technique was established that requires minimal equipment for field operations and optimizes the sampling procedure for field measurements. With an analysis time of less than 15 min, the compact GC-PID is ideal for field deployment of background and polluted atmospheres for near-real time measurements of BTEX. The results highlight the application of the compact and easily deployable GC-PID for community monitoring and screening of air toxics.

California's methane super-emitters.

Methane is a powerful greenhouse gas and is targeted for emissions mitigation by the US state of California and other jurisdictions worldwide1,2. Unique opportunities for mitigation are presented by point-source emitters-surface features or infrastructure components that are typically less than 10 metres in diameter and emit plumes of highly concentrated methane3. However, data on point-source emissions are sparse and typically lack sufficient spatial and temporal resolution to guide their mitigation and to accurately assess their magnitude4. Here we survey more than 272,000 infrastructure elements in California using an airborne imaging spectrometer that can rapidly map methane plumes5-7. We conduct five campaigns over several months from 2016 to 2018, spanning the oil and gas, manure-management and waste-management sectors, resulting in the detection, geolocation and quantification of emissions from 564 strong methane point sources. Our remote sensing approach enables the rapid and repeated assessment of large areas at high spatial resolution for a poorly characterized population of methane emitters that often appear intermittently and stochastically. We estimate net methane point-source emissions in California to be 0.618 teragrams per year (95 per cent confidence interval 0.523-0.725), equivalent to 34-46 per cent of the state's methane inventory8 for 2016. Methane 'super-emitter' activity occurs in every sector surveyed, with 10 per cent of point sources contributing roughly 60 per cent of point-source emissions-consistent with a study of the US Four Corners region that had a different sectoral mix9. The largest methane emitters in California are a subset of landfills, which exhibit persistent anomalous activity. Methane point-source emissions in California are dominated by landfills (41 per cent), followed by dairies (26 per cent) and the oil and gas sector (26 per cent). Our data have enabled the identification of the 0.2 per cent of California's infrastructure that is responsible for these emissions. Sharing these data with collaborating infrastructure operators has led to the mitigation of anomalous methane-emission activity10.

Carbon dioxide and methane measurements from the Los Angeles Megacity Carbon Project - Part 1: calibration, urban enhancements, and uncertainty estimates.

We report continuous surface observations of carbon dioxide (CO2) and methane (CH4) from the Los Angeles (LA) Megacity Carbon Project during 2015. We devised a calibration strategy, methods for selection of background air masses, calculation of urban enhancements, and a detailed algorithm for estimating uncertainties in urban-scale CO2 and CH4 measurements. These methods are essential for understanding carbon fluxes from the LA megacity and other complex urban environments globally. We estimate background mole fractions entering LA using observations from four "extra-urban" sites including two "marine" sites located south of LA in La Jolla (LJO) and offshore on San Clemente Island (SCI), one "continental" site located in Victorville (VIC), in the high desert northeast of LA, and one "continental/mid-troposphere" site located on Mount Wilson (MWO) in the San Gabriel Mountains. We find that a local marine background can be established to within ~1 ppm CO2 and ~10 ppb CH4 using these local measurement sites. Overall, atmospheric carbon dioxide and methane levels are highly variable across Los Angeles. "Urban" and "suburban" sites show moderate to large CO2 and CH4 enhancements relative to a marine background estimate. The USC (University of Southern California) site near downtown LA exhibits median hourly enhancements of ~20 ppm CO2 and ~150 ppb CH4 during 2015 as well as ~15 ppm CO2 and ~80 ppb CH4 during mid-afternoon hours (12:00-16:00 LT, local time), which is the typical period of focus for flux inversions. The estimated measurement uncertainty is typically better than 0.1 ppm CO2 and 1 ppb CH4 based on the repeated standard gas measurements from the LA sites during the last 2 years, similar to Andrews et al. (2014). The largest component of the measurement uncertainty is due to the single-point calibration method; however, the uncertainty in the background mole fraction is much larger than the measurement uncertainty. The background uncertainty for the marine background estimate is ~10 and ~15 % of the median mid-afternoon enhancement near downtown LA for CO2 and CH4, respectively. Overall, analytical and background uncertainties are small relative to the local CO2 and CH4 enhancements; however, our results suggest that reducing the uncertainty to less than 5 % of the median mid-afternoon enhancement will require detailed assessment of the impact of meteorology on background conditions.

Ecosystem-level controls on root-rhizosphere respiration.

Recent advances in the partitioning of autotrophic from heterotrophic respiration processes in soils in conjunction with new high temporal resolution soil respiration data sets offer insights into biotic and environmental controls of respiration. Besides temperature, many emerging controlling factors have not yet been incorporated into ecosystem-scale models. We synthesize recent research that has partitioned soil respiration into its process components to evaluate effects of nitrogen, temperature and photosynthesis on autotrophic flux from soils at the ecosystem level. Despite the widely used temperature dependence of root respiration, gross primary productivity (GPP) can explain most patterns of ecosystem root respiration (and to some extent heterotrophic respiration) at within-season time-scales. Specifically, heterotrophi crespiration is influenced by a seasonally variable supply of recent photosynthetic products in the rhizosphere. The contribution of stored root carbon (C) to root respiratory fluxes also varied seasonally, partially decoupling the proportion of photosynthetic C driving root respiration. In order to reflect recent insights, new hierarchical models, which incorporate root respiration as a primary function of GPP and which respond to environmental variables by modifying Callocation belowground, are needed for better prediction of future ecosystem C sequestration.

Warming accelerates decomposition of decades-old carbon in forest soils.

Global climate carbon-cycle models predict acceleration of soil organic carbon losses to the atmosphere with warming, but the size of this feedback is poorly known. The temperature sensitivity of soil carbon decomposition is commonly determined by measuring changes in the rate of carbon dioxide (CO(2)) production under controlled laboratory conditions. We added measurements of carbon isotopes in respired CO(2) to constrain the age of carbon substrates contributing to the temperature response of decomposition for surface soils from two temperate forest sites with very different overall rates of carbon cycling. Roughly one-third of the carbon respired at any temperature was fixed from the atmosphere more than 10 y ago, and the mean age of respired carbon reflected a mixture of substrates of varying ages. Consistent with global ecosystem model predictions, the temperature sensitivity of the carbon fixed more than a decade ago was the same as the temperature sensitivity for carbon fixed less than 10 y ago. However, we also observed an overall increase in the mean age of carbon respired at higher temperatures, even correcting for potential substrate limitation effects. The combination of several age constraints from carbon isotopes showed that warming had a similar effect on respiration of decades-old and younger (<10 y) carbon but a greater effect on decomposition of substrates of intermediate (between 7 and 13 y) age. Our results highlight the vulnerability of soil carbon to warming that is years-to-decades old, which makes up a large fraction of total soil carbon in forest soils globally.