Characterization of aerosol optical properties, chemical composition and mixing states in the winter season in Shanghai, China

Physical and chemical properties of ambient aerosols at the single particle level were studied in Shanghai from December 22 to 28, 2009. A Cavity-Ring-Down Aerosol Extinction Spectrometer（CRD-AES） and a nephelometer were deployed to measure aerosol light extinction and scattering properties, respectively. An Aerosol Time-of-Flight Mass Spectrometer（ATOFMS）was used to detect single particle sizes and chemical composition. Seven particle types were detected. Air parcels arrived at the sampling site from the vicinity of Shanghai until mid-day of December 25, when they started to originate from North China. The aerosol extinction,scattering, and absorption coefficients all dropped sharply when this cold, clean air arrived.Aerosol particles changed from a highly aged type before this meteorological shift to a relatively fresh type afterwards. The aerosol optical properties were dependent on the wind direction.Aerosols with high extinction coefficient and scattering Angstrom exponent（SAE） were observed when the wind blew from the west and northwest, indicating that they were predominantly fine particles. Nitrate and ammonium correlated most strongly with the change in aerosol optical properties. In the elemental carbon/organic carbon（ECOC） particle type, the diurnal trends of single scattering albedo（SSA） and elemental carbon（EC） signal intensity had a negative correlation. We also found a negative correlation（r =-0.87） between high mass-OC particle number fraction and the SSA in a relatively clean period, suggesting that particulate aromatic components might play an important role in light absorption in urban areas.     

Indirect benefits of symbiotic coccoids for an ant-defended myrmecophytic tree

The net benefits of mutualism depend directly on the costs and effectiveness of mutualistic services and indirectly on the interactions that affect those services. We examined interactions among Cordia alliodora myrmecophytic trees, their symbiotic ants Azteca pittieri, coccoid hemipterans, and foliar herbivores in two Neotropical dry forests. The tree makes two investments in symbiotic ants: it supplies nesting space, as domatia, and it provides phloem to coccoids, which then produce honeydew that is consumed by ants. Although higher densities of coccoids should have higher direct costs for trees, we asked whether higher densities of coccoids can also have higher indirect benefits for trees by increasing the effectiveness of ant defense against foliar herbivores. We found that trees benefited from ant defense against herbivores. Ants defended trees effectively only when colonies reached high densities within trees, and ant and coccoid densities within trees were strongly positively correlated. The benefits of reduced foliar herbivory by larger ant colonies were therefore indirectly controlled by the number of coccoids. Coccoid honeydew supply also affected per capita ant aggression against tree herbivores. Ants experimentally fed a carbohydrate-rich diet, analogous to sugar obtained from coccoids, were more aggressive against caterpillars per capita than ants fed a carbohydrate-poor diet. Ant defense was more effective on more valuable and vulnerable young leaves than on older leaves. Young domatia, associated with young leaves, contained higher coccoid densities than older domatia, which suggests that coccoids may also drive spatially favorable ant defense of the tree. If higher investments by one mutualistic partner are tied to higher benefits received from the other, there may be positive feedback between partners that will stabilize the mutualism. These results suggest that higher investment by trees in coccoids leads to more effective defense by ants against the tree's foliar herbivores.     

Modeling Human Factors That Affect the Loss of Biodiversity

Within conservation biology human factors are treated as driving forces of biodiversity loss, yet there are few empirical studies on how human actions affect biodiversity. We developed and tested an interdisciplinary model of biodiversity loss using socioeconomic and ecological data from 107 countries and structural equation modeling techniques. Some portions of the model fit the data well, other parts were less predictive. Counterintuitive results may be a result of the quality and availability of cross-national data and statistical limitations in testing a model of such complex processes. This model test provides insight into future research needs for examining human impacts on biodiversity. Issues including data quality, temporal and spatial scale, and model refinement are outlined. The results highlight the importance of relations between human social systems and biodiversity and the potential of interdisciplinary research.     

Critical Risk Indicators (CRIs) for the electric power grid: a survey and discussion of interconnected effects

The electric power grid is a critical societal resource connecting multiple infrastructural domains such as agriculture, transportation, and manufacturing. The electrical grid as an infrastructure is shaped by human activity and public policy in terms of demand and supply requirements. Further, the grid is subject to changes and stresses due to diverse factors including solar weather, climate, hydrology, and ecology. The emerging interconnected and complex network dependencies make such interactions increasingly dynamic, posing novel risks, and presenting new challenges to manage the coupled human–natural system. This paper provides a survey of models and methods that seek to explore the significant interconnected impact of the electric power grid and interdependent domains. We also provide relevant critical risk indicators (CRIs) across diverse domains that may be used to assess risks to electric grid reliability, including climate, ecology, hydrology, finance, space weather, and agriculture. We discuss the convergence of indicators from individual domains to explore possible systemic risk, i.e., holistic risk arising from cross-domain interconnections. Further, we propose a compositional approach to risk assessment that incorporates diverse domain expertise and information, data science, and computer science to identify domain-specific CRIs and their union in systemic risk indicators. Our study provides an important first step towards data-driven analysis and predictive modeling of risks in interconnected human–natural systems.

     

Spatial relationships between lead sources and children’s blood lead levels in the urban center of Indianapolis (USA)

Urban children remain disproportionately at risk of having higher blood lead levels than their suburban counterparts. The Westside Cooperative Organization (WESCO), located in Marion County, Indianapolis, Indiana, has a history of children with high blood lead levels as well as high soil lead (Pb) values. This study aims at determining the spatial relationship between soil Pb sources and children’s blood lead levels. Soils have been identified as a source of chronic Pb exposure to children, but the spatial scale of the source–recipient relationship is not well characterized. Neighborhood-wide analysis of soil Pb distribution along with a furnace filter technique for sampling interior Pb accumulation for selected homes (n = 7) in the WESCO community was performed. Blood lead levels for children aged 0–5 years during the period 1999–2008 were collected. The study population’s mean blood lead levels were higher than national averages across all ages, race, and gender. Non-Hispanic blacks and those individuals in the Wishard advantage program had the highest proportion of elevated blood lead levels. The results show that while there is not a direct relationship between soil Pb and children’s blood lead levels at a spatial scale of ~100 m, resuspension of locally sourced soil is occurring based on the interior Pb accumulation. County-wide, the largest predictor of elevated blood lead levels is the location within the urban core. Variation in soil Pb and blood lead levels on the community level is high and not predicted by housing stock age or income. Race is a strong predictor for blood lead levels in the WESCO community.