Quantifying Methane Emissions in the Uintah Basin During Wintertime Stagnation Episodes

This study presents a meteorologically-based methodology for quantifying basin-scale methane (CH4) emissions in Utah’s Uintah Basin, which is home to over 9,000 active and producing oil and natural gas wells. Previous studies in oil and gas producing regions have often relied on intensive aircraft campaigns to estimate methane emissions. However, the high cost of airborne campaigns prevents their frequent undertaking, thus providing only daytime snapshots of emissions rather than more temporally-representative estimates over multiple days. Providing estimates of CH4 emissions from oil and natural gas production regions across the United States is important to inform leakage rates and emission mitigation efforts in order to curb the potential impacts of these emissions on global climate change and local air quality assessments. Here we introduce the Basin-constrained Emissions Estimate (BEE) method, which utilizes the confining topography of a basin and known depth of a pollution layer during multi-day wintertime cold-air pool episodes to relate point observations of CH4 to basin-scale CH4 emission rates. This study utilizes ground-based CH4 observations from three fixed sites to calculate daily increases in CH4, a laser ceilometer to estimate pollution layer depth, and a Lagrangian transport model to assess the spatial representativity of surface observations. BEE was applied to two cold-air pool episodes during the winter of 2015–2016 and yielded CH4 emission estimates between 44.60 +/– 9.66 × 103 and 61.82 +/– 19.76 × 103 kg CH4 hr–1, which are similar to the estimates proposed by previous studies performed in the Uintah Basin. The techniques used in this study could potentially be utilized in other deep basins worldwide

Process-conditioned bias correction for seasonal forecasting: a case-study with ENSO in Peru

This work assesses the suitability of a first simple attempt for process-conditioned bias correction in the context of seasonal forecasting. To do this, we focus on the northwestern part of Peru and bias correct 1- and 4-month lead seasonal predictions of boreal winter (DJF) precipitation from the ECMWF System4 forecasting system for the period 1981–2010. In order to include information about the underlying large-scale circulation which may help to discriminate between precipitation affected by different processes, we introduce here an empirical quantile–quantile mapping method which runs conditioned on the state of the Southern Oscillation Index (SOI), which is accurately predicted by System4 and is known to affect the local climate. Beyond the reduction of model biases, our results show that the SOI-conditioned method yields better ROC skill scores and reliability than the raw model output over the entire region of study, whereas the standard unconditioned implementation provides no added value for any of these metrics. This suggests that conditioning the bias correction on simple but well-simulated large-scale processes relevant to the local climate may be a suitable approach for seasonal forecasting. Yet, further research on the suitability of the application of similar approaches to the one considered here for other regions, seasons and/or variables is needed.This work has received funding from the MULTI-SDM project (MINECO/FEDER, CGL2015-66583-R). The authors are grateful to SENAMHI for the observational data, which are publicly available from http://www.senamhi.gob.pe/?p=data-historica, and to the European Center for Medium-Range Weather Forecast (ECMWF), for the access to the System4 seasonal forecasting hindcast

Pacific climate variability and the possible impact on global surface CO2 flux

<p>Abstract</p> <p>Background</p> <p>Climate variability modifies both oceanic and terrestrial surface CO2 flux. Using observed/assimilated data sets, earlier studies have shown that tropical oceanic climate variability has strong impacts on the land surface temperature and soil moisture, and that there is a negative correlation between the oceanic and terrestrial CO2 fluxes. However, these data sets only cover less than the most recent 20 years and are insufficient for identifying decadal and longer periodic variabilities. To investigate possible impacts of interannual to interdecadal climate variability on CO2 flux exchange, the last 125 years of an earth system model (ESM) control run are examined.</p> <p>Results</p> <p>Global integration of the terrestrial CO2 flux anomaly shows variation much greater in amplitude and longer in periodic timescale than the oceanic flux. The terrestrial CO2 flux anomaly correlates negatively with the oceanic flux in some periods, but positively in others, as the periodic timescale is different between the two variables. To determine the spatial pattern of the variability, a series of composite analyses are performed. The results show that the oceanic CO2 flux variability peaks when the eastern tropical Pacific has a large sea surface temperature anomaly (SSTA). By contrast, the terrestrial CO2 flux variability peaks when the SSTA appears in the central tropical Pacific. The former pattern of variability resembles the ENSO-mode and the latter the ENSO-modoki¹.</p> <p>Conclusions</p> <p>Our results imply that the oceanic and terrestrial CO2 flux anomalies may correlate either positively or negatively depending on the relative phase of these two modes in the tropical Pacific.</p

Late Holocene climate: Natural or anthropogenic?

For more than a decade, scientists have argued about the warmth of the current interglaciation. Was the warmth of the preindustrial late Holocene natural in origin, the result of orbital changes that had not yet driven the system into a new glacial state? Or was it in considerable degree the result of humans intervening in the climate system through greenhouse gas emissions from early agriculture? Here we summarize new evidence that moves this debate forward by testing both hypotheses. By comparing late Holocene responses to those that occurred during previous interglaciations (in section 2), we assess whether the late Holocene responses look different (and thus anthropogenic) or similar (and thus natural). This comparison reveals anomalous (anthropogenic) signals. In section 3, we review paleoecological and archaeological syntheses that provide ground truth evidence on early anthropogenic releases of greenhouse gases. The available data document large early anthropogenic emissions consistent with the anthropogenic ice core anomalies, but more information is needed to constrain their size. A final section compares natural and anthropogenic interpretations of the δ13C trend in ice core CO2

Association between neighborhood need and spatial access to food stores and fast food restaurants in neighborhoods of Colonias

Objective To determine the extent to which neighborhood needs (socioeconomic deprivation and vehicle availability) are associated with two criteria of food environment access: 1) distance to the nearest food store and fast food restaurant and 2) coverage (number) of food stores and fast food restaurants within a specified network distance of neighborhood areas of colonias, using ground-truthed methods. Methods Data included locational points for 315 food stores and 204 fast food restaurants, and neighborhood characteristics from the 2000 U.S. Census for the 197 census block group (CBG) study area. Neighborhood deprivation and vehicle availability were calculated for each CBG. Minimum distance was determined by calculating network distance from the population-weighted center of each CBG to the nearest supercenter, supermarket, grocery, convenience store, dollar store, mass merchandiser, and fast food restaurant. Coverage was determined by calculating the number of each type of food store and fast food restaurant within a network distance of 1, 3, and 5 miles of each population-weighted CBG center. Neighborhood need and access were examined using Spearman ranked correlations, spatial autocorrelation, and multivariate regression models that adjusted for population density. Results Overall, neighborhoods had best access to convenience stores, fast food restaurants, and dollar stores. After adjusting for population density, residents in neighborhoods with increased deprivation had to travel a significantly greater distance to the nearest supercenter or supermarket, grocery store, mass merchandiser, dollar store, and pharmacy for food items. The results were quite different for association of need with the number of stores within 1 mile. Deprivation was only associated with fast food restaurants; greater deprivation was associated with fewer fast food restaurants within 1 mile. CBG with greater lack of vehicle availability had slightly better access to more supercenters or supermarkets, grocery stores, or fast food restaurants. Increasing deprivation was associated with decreasing numbers of grocery stores, mass merchandisers, dollar stores, and fast food restaurants within 3 miles. Conclusion It is important to understand not only the distance that people must travel to the nearest store to make a purchase, but also how many shopping opportunities they have in order to compare price, quality, and selection. Future research should examine how spatial access to the food environment influences the utilization of food stores and fast food restaurants, and the strategies used by low-income families to obtain food for the household

Focusing on fast food restaurants alone underestimates the relationship between neighborhood deprivation and exposure to fast food in a large rural area

<p>Abstract</p> <p>Background</p> <p>Individuals and families are relying more on food prepared outside the home as a source for at-home and away-from-home consumption. Restricting the estimation of fast-food access to fast-food restaurants alone may underestimate potential spatial access to fast food.</p> <p>Methods</p> <p>The study used data from the 2006 Brazos Valley Food Environment Project (BVFEP) and the 2000 U.S. Census Summary File 3 for six rural counties in the Texas Brazos Valley region. BVFEP ground-truthed data included identification and geocoding of all fast-food restaurants, convenience stores, supermarkets, and grocery stores in study area and on-site assessment of the availability and variety of fast-food lunch/dinner entrées and side dishes. Network distance was calculated from the population-weighted centroid of each census block group to all retail locations that marketed fast food (<it>n </it>= 205 fast-food opportunities).</p> <p>Results</p> <p>Spatial access to fast-food opportunities (FFO) was significantly better than to traditional fast-food restaurants (FFR). The median distance to the nearest FFO was 2.7 miles, compared with 4.5 miles to the nearest FFR. Residents of high deprivation neighborhoods had better spatial access to a variety of healthier fast-food entrée and side dish options than residents of low deprivation neighborhoods.</p> <p>Conclusions</p> <p>Our analyses revealed that identifying fast-food restaurants as the sole source of fast-food entrées and side dishes underestimated neighborhood exposure to fast food, in terms of both neighborhood proximity and coverage. Potential interventions must consider all retail opportunities for fast food, and not just traditional FFR.</p

A path forward in the debate over health impacts of endocrine disrupting chemicals

Several recent publications reflect debate on the issue of “endocrine disrupting chemicals” (EDCs), indicating that two seemingly mutually exclusive perspectives are being articulated separately and independently. Considering this, a group of scientists with expertise in basic science, medicine and risk assessment reviewed the various aspects of the debate to identify the most significant areas of dispute and to propose a path forward. We identified four areas of debate. The first is about the definitions for terms such as “endocrine disrupting chemical”, “adverse effects”, and “endocrine system”. The second is focused on elements of hormone action including “potency”, “endpoints”, “timing”, “dose” and “thresholds”. The third addresses the information needed to establish sufficient evidence of harm. Finally, the fourth focuses on the need to develop and the characteristics of transparent, systematic methods to review the EDC literature. Herein we identify areas of general consensus and propose resolutions for these four areas that would allow the field to move beyond the current and, in our opinion, ineffective debate