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Agricultural adaptation to climate change is critical for ensuring future food security. Social capital is important for climate change adaptation, but institutions and social networks at multiple scales (e.g., household, community, and institution) have been overlooked in studying agricultural climate change adaptation. We combine data from 13 sites in 11 low-income countries in East Africa, West Africa, and South Asia to explore how multiple scales of social capital relate to household food security outcomes among smallholder farmers. Using social network theory, we define three community organizational social network types (fragmented defined by lack of coordination, brokered defined as having a strong central actor, or shared defined by high coordination) and examine household social capital through group memberships. We find community and household social capital are positively related, with higher household group membership more likely in brokered and shared networks. Household group membership is associated with more than a 10% reduction in average months of food insecurity, an effect moderated by community social network type. In communities with fragmented and shared organizational networks, additional household group memberships is associated with consistent decreases in food insecurity, in some cases up to two months; whereas in brokered networks, reductions in food insecurity are only associated with membership in credit groups. These effects are confirmed by hierarchical random effects models, which control for demographic factors. This suggests that multiple scales of social capital—both within and outside the household—are correlated with household food security. This social capital may both be bridging (across groups) and bonding (within groups) with different implications for how social capital structure affects food security. Efforts to improve food security could recognize the potential for both household and community level social networks and collaboration, which further research can capture by analyzing multiple scales of social capital data.

Atmospheric methane (CH4) is a potent greenhouse gas, and its mole fraction has more than doubled since the preindustrial era. Fossil fuel extraction and use are among the largest anthropogenic sources of CH4 emissions, but the precise magnitude of these contributions is a subject of debate. Carbon-14 in CH4 (14CH4) can be used to distinguish between fossil (14C-free) CH4 emissions and contemporaneous biogenic sources; however, poorly constrained direct 14CH4 emissions from nuclear reactors have complicated this approach since the middle of the 20th century. Moreover, the partitioning of total fossil CH4 emissions (presently 172 to 195 teragrams CH4 per year) between anthropogenic and natural geological sources (such as seeps and mud volcanoes) is under debate; emission inventories suggest that the latter account for about 40 to 60 teragrams CH4 per year. Geological emissions were less than 15.4 teragrams CH4 per year at the end of the Pleistocene, about 11,600 years ago, but that period is an imperfect analogue for present-day emissions owing to the large terrestrial ice sheet cover, lower sea level and extensive permafrost. Here we use preindustrial-era ice core 14CH4 measurements to show that natural geological CH4 emissions to the atmosphere were about 1.6 teragrams CH4 per year, with a maximum of 5.4 teragrams CH4 per year (95 per cent confidence limit)—an order of magnitude lower than the currently used estimates. This result indicates that anthropogenic fossil CH4 emissions are underestimated by about 38 to 58 teragrams CH4 per year, or about 25 to 40 per cent of recent estimates. Our record highlights the human impact on the atmosphere and climate, provides a firm target for inventories of the global CH4 budget, and will help to inform strategies for targeted emission reductions.

Abstract The albedo of a roof determines the fraction of incoming sunlight that is reflected, which affects heat transfer into the building and exchange of energy between the built environment and the atmosphere. While the albedo of individual roofs can be easily measured, roof albedo at the city scale is unknown. In this paper we characterize the albedos of roofs in seven cities in California: Los Angeles, Long Beach, Bakersfield, San Francisco, San Jose, Sacramento, and San Diego. The fraction of urban area covered by roofs ranged by city from 10% to 25%. City-wide average roof albedo ranged from 0.17 ± 0.08 to 0.20 ± 0.11 (mean ± standard deviation) for five of the cities; values were higher in Sacramento (0.24 ± 0.11) and San Diego (0.29 ± 0.15). Buildings with small roofs were found to constitute a large fraction of city roof area and to have low mean albedos. This suggests that efforts to increase urban albedo through the use of reflective roofs should include small roofs, which are presumably mostly residential. Roof albedos derived for Bakersfield were used in a regional climate model (Weather Research and Forecasting Model) to estimate temperature changes attainable by converting the current stock of roofs to “cool” high albedo roofs. It was found that seasonal mean afternoon (15:00 LST) temperatures could be reduced by up to 0.2 °C during both the summer and winter. Changes in precipitation were not significant at the 95% confidence level.

We utilize a variety of climate datasets to examine impacts of two mechanisms on precipitation in the Greater Horn of Africa (GHA) during northern-hemisphere summer. First, surface-pressure gradients draw moist air toward the GHA from the tropical Atlantic Ocean and Congo Basin. Variability of the strength of these gradients strongly influences GHA precipitation totals and accounts for important phenomena such as the 1960s–1980s rainfall decline and devastating 1984 drought. Following the 1980s, precipitation variability became increasingly influenced by the southern tropical Indian Ocean (STIO) region. Within this region, increases in sea-surface temperature, evaporation, and precipitation are linked with increased exports of dry mid-tropospheric air from the STIO region toward the GHA. Convergence of dry air above the GHA reduces local convection and precipitation. It also produces a clockwise circulation response near the ground that reduces moisture transports from the Congo Basin. Because precipitation originating in the Congo Basin has a unique isotopic signature, records of moisture transports from the Congo Basin may be preserved in the isotopic composition of annual tree rings in the Ethiopian Highlands. A negative trend in tree-ring oxygen-18 during the past half century suggests a decline in the proportion of precipitation originating from the Congo Basin. This trend may not be part of a natural cycle that will soon rebound because climate models characterize Indian Ocean warming as a principal signature of greenhouse-gas induced climate change. We therefore expect surface warming in the STIO region to continue to negatively impact GHA precipitation during northern-hemisphere summer.

Integrated assessment models show that, without new climate policies, abundant supplies of natural gas will have little impact on greenhouse-gas emissions and climate change. See Letter p.482 The development of hydraulic fracturing technologies has led to rapid growth in the use natural gas as an energy source. Some evidence has suggested that this growing adoption of natural gas might lead to a reduced greenhouse gas burden and consequent mitigation of climate change. This collaboration between five energy–climate modelling teams show that instead — under a scenario of abundant natural gas availability — increased consumption will have little or no impact on climate change. The authors suggest that expanded natural gas production and use is neither a substitute for a climate policy in the decades ahead nor a major new complication to the anthropogenic emissions problem.

Reoxidation and mobilization of previously reduced and immobilized uranium by dissolved-phase oxidants poses a significant challenge for remediating uranium-contaminated groundwater. Preferential oxidation of reduced sulfur-bearing species, as opposed to reduced uranium-bearing species, has been demonstrated to limit the mobility of uranium at the laboratory scale yet field-scale investigations are lacking. In this study, the mobility of uranium in the presence of nitrate oxidant was investigated in a shallow groundwater system after establishing conditions conducive to uranium reduction and the formation of reduced sulfur-bearing species. A series of three injections of groundwater (200 L) containing U(VI) (5 μM) and amended with ethanol (40 mM) and sulfate (20 mM) were conducted in ten test wells in order to stimulate microbial-mediated reduction of uranium and the formation of reduced sulfur-bearing species. Simultaneous push-pull tests were then conducted in triplicate well clusters to investigate the mobility of U(VI) under three conditions: 1) high nitrate (120 mM), 2) high nitrate (120 mM) with ethanol (30 mM), and 3) low nitrate (2 mM) with ethanol (30 mM). Dilution-adjusted breakthrough curves of ethanol, nitrate, nitrite, sulfate, and U(VI) suggested that nitrate reduction was predominantly coupled to the oxidation of reduced-sulfur bearing species, as opposed to the reoxidation of U(IV), under all three conditions for the duration of the 36-day tests. The amount of sulfate, but not U(VI), recovered during the push-pull tests was substantially more than injected, relative to bromide tracer, under all three conditions and further suggested that reduced sulfur-bearing species were preferentially oxidized under nitrate-reducing conditions. However, some reoxidation of U(IV) was observed under nitrate-reducing conditions and in the absence of detectable nitrate and/or nitrite. This suggested that reduced sulfur-bearing species may not be fully effective at limiting the mobility of uranium in the presence of dissolved and/or solid-phase oxidants. The results of this field study confirmed those of previous laboratory studies which suggested that reoxidation of uranium under nitrate-reducing conditions can be substantially limited by preferential oxidation of reduced sulfur-bearing species.

Author(s): Doughty, C; Oldenburg, CM | Abstract: Uncertainty in the long-term fate of CO2 injected for geologic carbon sequestration (GCS) is a significant barrier to the adoption of GCS as a greenhouse-gas emission-mitigation for industry and regulatory agencies alike. We present a modeling study that demonstrates that the uncertainty in forecasts of GCS site performance decreases over time as monitoring data are used to update operational models. We consider a case study of GCS in a depleted natural gas reservoir, with CO2 injection occurring over 20 years, with a 50-year post-injection site care period. We constructed a detailed model to generate the actual model output, which is considered synthetic observation data. A series of simpler operational models based on limited data and assumptions about how an operator would model such a site are then run and compared against actual model output at specific monitoring points after one year, two years, etc. The operational model is updated and improved using the synthetic observation data from the actual model at the same time intervals. Model parameter values and model features needed to be updated over time to improve matches to the actual model. These kinds of model adjustments would be a normal part of reservoir engineering and site management at GCS sites. Uncertainty in two key measures related to site performance decreases with time: extent of the CO2 plume up-dip migration, and radial extent of the pressure pulse. This conclusion should help allay the concerns of industry and regulators about uncertainty in long-term fate of CO2 at GCS sites.

While science matters for environmental management, creating science that is credible, salient to decision-makers, and deemed legitimate by stakeholders is challenging. Collaborative modeling is an increasingly-used approach to enable effective science-based decision-making. This work evaluates the modeling process conducted for two hydropower dam licensing negotiations, to explore how differences in the collaborative development of hydrological models affected differences in their use in subsequent decision-making. In one case, the model was developed iteratively through deliberation with stakeholders. Consequently, stakeholders understood the model and its limitations and trusted the model and modelers; the model itself was also better designed to evaluate resource managers’ questions. The collaboratively-developed model became the focal point for subsequent negotiations and enabled creative group problem-solving. Conversely, in the case with less engagement during model development, the model was not used subsequently by decision-makers. These differences are argued to result from trust built during the modeling process, applicability of the model to test real management scenarios, and the broader social context in which the models were used.