Environmental Injustices of Leaks from Urban Natural Gas Distribution Systems: Patterns among and within 13 U.S. Metro Areas.

Natural gas leaks in local distribution systems can develop as underground pipeline infrastructure degrades over time. These leaks lead to safety, economic, and climate change burdens on society. We develop an environmental justice analysis of natural gas leaks discovered using advanced leak detection in 13 U.S. metropolitan areas. We use Bayesian spatial regression models to study the relationship between the density of leak indications and sociodemographic indicators in census tracts. Across all metro areas combined, we found that leak densities increase with increasing percent people of color and with decreasing median household income. These patterns of infrastructure injustice also existed within most metro areas, even after accounting for housing age and the spatial structure of the data. Considering the injustices described here, we identify actions available to utilities, regulators, and advocacy groups that can be taken to improve the equity of local natural gas distribution systems.

Deficit irrigation impacts on greenhouse gas emissions under drip-fertigated maize in the Great Plains of Colorado.

Precise water and fertilizer application can increase crop water productivity and reduce agricultural contributions to greenhouse gas (GHG) emissions. Regulated deficit irrigation (DI) and drip fertigation control the amount, location, and timing of water and nutrient application. Yet, few studies have measured GHG emissions under these practices, especially for maize (Zea mays L.). The objective was to quantify N2 O and CO2 emission from DI and full irrigation (FI) within a drip-fertigated maize system in northeastern Colorado. During two growing seasons of measurement, treatments consisted of mild, moderate, and extreme DI and FI. Deficit irrigation was managed based on growth stage so that full evapotranspiration (ET) was met during the yield-sensitive reproductive stage, but less than full crop ET was applied during the late vegetative and maturation growth stages. In the first year, mild DI (90% ET) reduced N2 O emissions by 50% compared with FI. In the second year, compared with FI, moderate DI (69-80% ET) reduced N2 O emissions by 15%, and extreme DI (54-68% ET) reduced N2 O emissions by 40%. Only extreme DI in the second year significantly reduced CO2 emissions (by 30%) compared with FI. Mild DI reduced yield-scaled emissions in the first year, but moderate and extreme DI had similar yield-scaled emissions as FI in the second year. The surface drip fertigation resulted in total GHG emissions that were one-tenth of literature-based measurements from sprinkler-irrigated maize systems. This study illustrates the potential of DI and drip fertigation to reduce N2 O and CO2 emissions in irrigated cropping systems.

Using isotope pool dilution to understand how organic carbon additions affect N2 O consumption in diverse soils.

Nitrous oxide (N2 O) is a formidable greenhouse gas with a warming potential ~300× greater than CO2 . However, its emissions to the atmosphere have gone largely unchecked because the microbial and environmental controls governing N2 O emissions have proven difficult to manage. The microbial process N2 O consumption is the only know biotic pathway to remove N2 O from soil pores and therefore reduce N2 O emissions. Consequently, manipulating soils to increase N2 O consumption by organic carbon (OC) additions has steadily gained interest. However, the response of N2 O emissions to different OC additions are inconsistent, and it is unclear if lower N2 O emissions are due to increased consumption, decreased production, or both. Simplified and systematic studies are needed to evaluate the efficacy of different OC additions on N2 O consumption. We aimed to manipulate N2 O consumption by amending soils with OC compounds (succinate, acetate, propionate) more directly available to denitrifiers. We hypothesized that N2 O consumption is OC-limited and predicted these denitrifier-targeted additions would lead to enhanced N2 O consumption and increased nosZ gene abundance. We incubated diverse soils in the laboratory and performed a 15 N2 O isotope pool dilution assay to disentangle microbial N2 O emissions from consumption using laser-based spectroscopy. We found that amending soils with OC increased gross N2 O consumption in six of eight soils tested. Furthermore, three of eight soils showed Increased N2 O Consumption and Decreased N2 O Emissions (ICDE), a phenomenon we introduce in this study as an N2 O management ideal. All three ICDE soils had low soil OC content, suggesting ICDE is a response to relaxed C-limitation wherein C additions promote soil anoxia, consequently stimulating the reduction of N2 O via denitrification. We suggest, generally, OC additions to low OC soils will reduce N2 O emissions via ICDE. Future studies should prioritize methodical assessment of different, specific, OC-additions to determine which additions show ICDE in different soils.

An approach for calibrating laser-based N2 O isotopic analyzers for soil biogeochemistry research.

RATIONALE: Technological advances have motivated researchers to transition from traditional gas chromatography/isotope ratio mass spectrometry to rapid, high-throughput, laser-based instrumentation for N2 O isotopic research. However, calibrating laser-based instruments to yield accurate and precise isotope ratios has been an ongoing challenge. To streamline the N2 O isotope research pipeline, we developed the calibration protocol for laser-based analyzers described here. While our approach is targeted at laboratory soil incubations, we anticipate that it will be broadly applicable for diverse types of stable isotope research. METHODS: We prepared standards diluted from USGS52 and from a commercial cylinder to develop a calibration curve spanning from 0.3 to 300 ppm N2 O. To calibrate over this broad range, we binned each isotopocule (N2 O, N15 NO, 15 NNO, and NN18 O) into low, medium, and high concentration ranges and then used mathematically similar polynomial functions to calibrate the isotopocules within each concentration range. We also assessed the temporal stability of the instrument and the capacity for our calibration approach to work with isotopically enriched gas samples. RESULTS: Our calibration approach yielded generally accurate and precise data when isotopocules were calibrated in concentration ranges, and the measurements appeared to be temporally stable. For all isotopocules at natural abundance, the residual percentage error was smallest in the medium N2 O range. There was more noise in the corrected isotopomers and isotopologue at natural abundance in samples with the lowest and highest N2 O concentrations. Corrected isotopomer results from isotopically enriched samples were very precise. CONCLUSIONS: Developing our calibration strategy involved learning several key lessons: (1) calibrate isotopocules in distinct concentration ranges, (2) use mathematically similar models to calibrate the isotopocules in each range, (3) calibrated N2 O concentrations and δ values tend to be most accurate and precise in the medium N2 O range, and (4) we encourage users to take advantage of isotopic enrichment to capitalize on laser-based instrument strengths.

A National Estimate of Methane Leakage from Pipeline Mains in Natural Gas Local Distribution Systems.

We estimate methane emissions from U.S. local distribution natural gas (NG) pipes using data collected from an advanced mobile leak detection (AMLD) platform. We estimate that there are 630,000 leaks in U.S. distribution mains, resulting in methane emissions of 0.69 Tg/year (95% cr int: 0.25, 1.23). Total emissions are calculated as the product of activity factors and emissions factors. Our analysis leveraged data on >4000 leak indications found using AMLD, combined with utility pipeline GIS information, to allow us to estimate activity factors. We derive emissions factors from AMLD emission rate estimates and correct these emissions factors based on data from in-field studies assessing AMLD emissions estimates. Finally, we quantify uncertainty in both emissions factors and activity factors and propagate the uncertainty to our total emissions estimate. In modeling leak frequency, we find a clear interaction between pipeline material and age with the leakiness of all material types increasing with age. Our national methane emissions estimate is approximately 5× greater (95% cr int: 1.7×, 8.7×) than the U.S. Environmental Protection Agency's current greenhouse gas inventory estimate for pipeline mains in local distribution systems due to both a larger estimated number of leaks and better characterization of the upper tail of the skewed distribution of emission rates.

Embracing a new paradigm for temperature sensitivity of soil microbes.

The temperature sensitivity of soil processes is of major interest, especially in light of climate change. Originally formulated to explain the temperature dependence of chemical reactions, the Arrhenius equation, and related Q10 temperature coefficient, has a long history of application to soil biological processes. However, empirical data indicate that Q10 and Arrhenius model are often poor metrics of temperature sensitivity in soils. In this opinion piece, we aim to (a) review alternative approaches for characterizing temperature sensitivity, focusing on macromolecular rate theory (MMRT); (b) provide strategies and tools for implementing a new temperature sensitivity framework; (c) develop thermal adaptation hypotheses for the MMRT framework; and (d) explore new questions and opportunities stemming from this paradigm shift. Microbial ecologists should consider developing and adopting MMRT as the basis for predicting biological rates as a function of temperature. Improved understanding of temperature sensitivity in soils is particularly pertinent as microbial response to temperature has a large impact on global climate feedbacks.

Rapid nitrogen fixation by canopy microbiome in tropical forest determined by both phosphorus and molybdenum.

Biological nitrogen fixation is critical for the nitrogen cycle of tropical forests, yet we know little about the factors that control the microbial nitrogen fixers that colonize the microbiome of leaves and branches that make up a forest canopy. Forest canopies are especially prone to nutrient limitation because they are (1) disconnected from soil nutrient pools and (2) often subject to leaching. Earlier studies have suggested a role of phosphorus and molybdenum in controlling biological N-fixation rates, but experimental confirmation has hitherto been unavailable. Here we present the results of a manipulation of canopy nutrient availability. Our findings demonstrate a primary role of phosphorus in constraining overall N fixation by canopy cyanobacteria, but also a secondary role of molybdenum in determining per-cell fixation rates. A conservative evaluation suggests that canopy fixation can contribute to significant N fluxes at the ecosystem level, especially as bursts following atmospheric inputs of nutrient-rich dust.

An open source algorithm to detect natural gas leaks from mobile methane survey data.

The data collected by mobile methane (CH4) sensors can be used to find natural gas (NG) leaks in urban distribution systems. Extracting actionable insights from the large volumes of data collected by these sensors requires several data processing steps. While these survey platforms are commercially available, the associated data processing software largely constitute a black box due to their proprietary nature. In this paper we describe a step-by-step algorithm for developing leak indications using data from mobile CH4 surveys, providing an under-the-hood look at the choices and challenges associated with data analysis. We also describe how our algorithm has evolved over time, and the data-driven insights that have prompted these changes. Applying our algorithm to data collected in 15 cities produced more than 6100 leak indications and estimates of the leaks' size. We use these results to characterize the distribution of leak sizes in local NG distribution systems. Mobile surveys are already an effective and necessary tool for managing NG distribution systems, but improvements in the technology and software will continue to increase its value.

Vehicle-Based Methane Surveys for Finding Natural Gas Leaks and Estimating Their Size: Validation and Uncertainty.

Managing leaks in urban natural gas (NG) distribution systems is important for reducing methane emissions and costly waste. Mobile surveying technologies have emerged as a new tool for monitoring system integrity, but this new technology has not yet been widely adopted. Here, we establish the efficacy of mobile methane surveys for managing local NG distribution systems by evaluating their ability to detect and locate NG leaks and quantify their emissions. In two cities, three-quarters of leak indications from mobile surveys corresponded to NG leaks, but local distribution companies' field crews did not find most of these leaks, indicating that the national CH4 activity factor for leaks in local NG distribution pipelines is underestimated by a factor of 2.4. We found the median distance between mobile-estimated leak locations and actual leak locations was 19 m. A comparison of emission quantification methods (mobile-based, surface enclosure, and tracer ratio) found that the mobile method overestimated leak magnitude for the smallest leaks but accurately estimated size for the largest leaks that are responsible for the majority of total emissions. Across leak sizes, mobile methods adequately rank relative emission rates for repair prioritization, and they are easily deployed and offer efficient spatial coverage.

A meta-analysis of temperature sensitivity as a microbial trait.

Traits-based approaches in microbial ecology provide a valuable way to abstract organismal interaction with the environment and to generate hypotheses about community function. Using macromolecular rate theory (MMRT), we recently identified that temperature sensitivity can be characterized as a distinct microbial trait. As temperature is fundamental in controlling biological reactions, variation in temperature sensitivity across communities, organisms, and processes has the potential to vastly improve understanding of microbial response to climate change. These microbial temperature sensitivity traits include the heat capacity ( ΔCP‡ ), temperature optimum (Topt ), and point of maximum temperature sensitivity (TSmax ), each of which provide unique insights about organismal response to changes in temperature. In this meta-analysis, we analyzed the distribution of these temperature sensitivity traits from bacteria, fungi, and mixed communities across a variety of biological systems (e.g., soils, oceans, foods, wastewater treatment plants) in order to identify commonalities in temperature responses across these diverse organisms and reaction rates. Our analysis of temperature sensitivity traits from over 350 temperature response curves reveals a wide distribution of temperature sensitivity traits, with Topt and TSmax well within biological relevant temperatures. We find that traits vary significantly depending on organism type, microbial diversity, source environment, and biological process, with higher temperature sensitivity found in fungi than bacteria and in less diverse systems. Carbon dioxide production was found to be less temperature sensitive than denitrification, suggesting that changes in temperature will have a potentially larger impact on nitrogen-related processes. As climate changes, these results have important implications for basic understanding of the temperature sensitivity of biological reactions and for ecological understanding of species' trait distributions, as well as for improved treatment of temperature sensitivity in models.

Rapid, Vehicle-Based Identification of Location and Magnitude of Urban Natural Gas Pipeline Leaks.

Information about the location and magnitudes of natural gas (NG) leaks from urban distribution pipelines is important for minimizing greenhouse gas emissions and optimizing investment in pipeline management. To enable rapid collection of such data, we developed a relatively simple method using high-precision methane analyzers in Google Street View cars. Our data indicate that this automated leak survey system can document patterns in leak location and magnitude within and among cities, even without wind data. We found that urban areas with prevalent corrosion-prone distribution lines (Boston, MA, Staten Island, NY, and Syracuse, NY), leaked approximately 25-fold more methane than cities with more modern pipeline materials (Burlington, VT, and Indianapolis, IN). Although this mobile monitoring method produces conservative estimates of leak rates and leak counts, it can still help prioritize both leak repairs and replacement of leak-prone sections of distribution lines, thus minimizing methane emissions over short and long terms.

Temperature Sensitivity as a Microbial Trait Using Parameters from Macromolecular Rate Theory.

The activity of soil microbial extracellular enzymes is strongly controlled by temperature, yet the degree to which temperature sensitivity varies by microbe and enzyme type is unclear. Such information would allow soil microbial enzymes to be incorporated in a traits-based framework to improve prediction of ecosystem response to global change. If temperature sensitivity varies for specific soil enzymes, then determining the underlying causes of variation in temperature sensitivity of these enzymes will provide fundamental insights for predicting nutrient dynamics belowground. In this study, we characterized how both microbial taxonomic variation as well as substrate type affects temperature sensitivity. We measured ß-glucosidase, leucine aminopeptidase, and phosphatase activities at six temperatures: 4, 11, 25, 35, 45, and 60°C, for seven different soil microbial isolates. To calculate temperature sensitivity, we employed two models, Arrhenius, which predicts an exponential increase in reaction rate with temperature, and Macromolecular Rate Theory (MMRT), which predicts rate to peak and then decline as temperature increases. We found MMRT provided a more accurate fit and allowed for more nuanced interpretation of temperature sensitivity in all of the enzyme × isolate combinations tested. Our results revealed that both the enzyme type and soil isolate type explain variation in parameters associated with temperature sensitivity. Because we found temperature sensitivity to be an inherent and variable property of an enzyme, we argue that it can be incorporated as a microbial functional trait, but only when using the MMRT definition of temperature sensitivity. We show that the Arrhenius metrics of temperature sensitivity are overly sensitive to test conditions, with activation energy changing depending on the temperature range it was calculated within. Thus, we propose the use of the MMRT definition of temperature sensitivity for accurate interpretation of temperature sensitivity of soil microbial enzymes.

Multigas Leakage Correction in Static Environmental Chambers Using Sulfur Hexafluoride and Raman Spectroscopy.

In static environmental chamber experiments, the precision of gas flux measurements can be significantly improved by a thorough gas leakage correction to avoid under- or overestimation of biological activity such as respiration or photosynthesis. Especially in the case of small biological net gas exchange rates or gas accumulation phases during long environmental monitoring experiments, gas leakage fluxes could distort the analysis of the biogenic gas kinetics. Here we propose and demonstrate a general protocol for online correction of diffusion-driven gas leakage in plant chambers by simultaneous quantification of the inert tracer sulfur hexafluoride (SF6) and the investigated biogenic gases using enhanced Raman spectroscopy. By quantifying the leakage rates of carbon dioxide (CO2), methane (CH4), and hydrogen (H2) simultaneously with SF6 in the test chamber, their effective diffusivity ratios of approximately 1.60, 1.96, and 5.65 were determined, each related to SF6. Because our experiments suggest that the effective diffusivity ratios are reproducible for an individual static environmental chamber, even under varying concentration gradients and slight changes of the chamber sealing, an experimental method to quantify gas leakage fluxes by using effective diffusivity ratios and SF6 leakage fluxes is proposed. The method is demonstrated by quantifying the CO2 net exchange rate of a plant-soil ecosystem (Mirabilis jalapa). By knowing the effective chamber diffusivity ratio CO2/SF6 and the measured SF6 leakage rate during the experiment, the leakage contribution to the total CO2 exchange rate could be calculated and the biological net CO2 concentration change within the chamber atmosphere determined.

Contrasting above- and belowground sensitivity of three Great Plains grasslands to altered rainfall regimes.

Intensification of the global hydrological cycle with atmospheric warming is expected to increase interannual variation in precipitation amount and the frequency of extreme precipitation events. Although studies in grasslands have shown sensitivity of aboveground net primary productivity (ANPP) to both precipitation amount and event size, we lack equivalent knowledge for responses of belowground net primary productivity (BNPP) and NPP. We conducted a 2-year experiment in three US Great Plains grasslands--the C4-dominated shortgrass prairie (SGP; low ANPP) and tallgrass prairie (TGP; high ANPP), and the C3-dominated northern mixed grass prairie (NMP; intermediate ANPP)--to test three predictions: (i) both ANPP and BNPP responses to increased precipitation amount would vary inversely with mean annual precipitation (MAP) and site productivity; (ii) increased numbers of extreme rainfall events during high-rainfall years would affect high and low MAP sites differently; and (iii) responses belowground would mirror those aboveground. We increased growing season precipitation by as much as 50% by augmenting natural rainfall via (i) many (11-13) small or (ii) fewer (3-5) large watering events, with the latter coinciding with naturally occurring large storms. Both ANPP and BNPP increased with water addition in the two C4 grasslands, with greater ANPP sensitivity in TGP, but greater BNPP and NPP sensitivity in SGP. ANPP and BNPP did not respond to any rainfall manipulations in the C3 -dominated NMP. Consistent with previous studies, fewer larger (extreme) rainfall events increased ANPP relative to many small events in SGP, but event size had no effect in TGP. Neither system responded consistently above- and belowground to event size; consequently, total NPP was insensitive to event size. The diversity of responses observed in these three grassland types underscores the challenge of predicting responses relevant to C cycling to forecast changes in precipitation regimes even within relatively homogeneous biomes such as grasslands.

Nitrogen cycling and water pulses in semiarid grasslands: are microbial and plant processes temporally asynchronous?

Precipitation pulses in arid ecosystems can lead to temporal asynchrony in microbial and plant processing of nitrogen (N) during drying/wetting cycles causing increased N loss. In contrast, more consistent availability of soil moisture in mesic ecosystems can synchronize microbial and plant processes during the growing season, thus minimizing N loss. We tested whether microbial N cycling is asynchronous with plant N uptake in a semiarid grassland. Using (15)N tracers, we compared rates of N cycling by microbes and N uptake by plants after water pulses of 1 and 2 cm to rates in control plots without a water pulse. Microbial N immobilization, gross N mineralization, and nitrification dramatically increased 1-3 days after the water pulses, with greatest responses after the 2-cm pulse. In contrast, plant N uptake increased more after the 1-cm than after the 2-cm pulse. Both microbial and plant responses reverted to control levels within 10 days, indicating that both microbial and plant responses were short lived. Thus, microbial and plant processes were temporally synchronous following a water pulse in this semiarid grassland, but the magnitude of the pulse substantially influenced whether plants or microbes were more effective in acquiring N. Furthermore, N loss increased after both small and large water pulses (as shown by a decrease in total (15)N recovery), indicating that changes in precipitation event sizes with future climate change could exacerbate N losses from semiarid ecosystems.