Selection of a network of large lakes and reservoirs suitable for global environmental change analysis using Earth Observation

The GloboLakes project, a global observatory of lake responses to environmental change, aims to exploit current satellite missions and long remote-sensing archives to synoptically study multiple lake ecosystems, assess their current condition, reconstruct past trends to system trajectories, and assess lake sensitivity to multiple drivers of change. Here we describe the selection protocol for including lakes in the global observatory based upon remote-sensing techniques and an initial pool of the largest 3721 lakes and reservoirs in the world, as listed in the Global Lakes and Wetlands Database. An 18-year-long archive of satellite data was used to create spatial and temporal filters for the identification of waterbodies that are appropriate for remote-sensing methods. Further criteria were applied and tested to ensure the candidate sites span a wide range of ecological settings and characteristics; a total 960 lakes, lagoons, and reservoirs were selected. The methodology proposed here is applicable to new generation satellites, such as the European Space Agency Sentinel-series.

Enhanced Volatile Organic Compounds emissions and organic aerosol mass increase the oligomer content of atmospheric aerosols

Secondary organic aerosol (SOA) accounts for a dominant fraction of the submicron atmospheric particle mass, but knowledge of the formation, composition and climate effects of SOA is incomplete and limits our understanding of overall aerosol effects in the atmosphere. Organic oligomers were discovered as dominant components in SOA over a decade ago in laboratory experiments and have since been proposed to play a dominant role in many aerosol processes. However, it remains unclear whether oligomers are relevant under ambient atmospheric conditions because they are often not clearly observed in field samples. Here we resolve this long-standing discrepancy by showing that elevated SOA mass is one of the key drivers of oligomer formation in the ambient atmosphere and laboratory experiments. We show for the first time that a specific organic compound class in aerosols, oligomers, is strongly correlated with cloud condensation nuclei (CCN) activities of SOA particles. These findings might have important implications for future climate scenarios where increased temperatures cause higher biogenic volatile organic compound (VOC) emissions, which in turn lead to higher SOA mass formation and significant changes in SOA composition. Such processes would need to be considered in climate models for a realistic representation of future aerosol-climate-biosphere feedbacks.

Cross-sectoral differences in the drivers of innovation: evidence from the Irish Community Innovation Survey

Purpose: The purpose of this paper is to analyse differences in the drivers of firm innovation performance across sectors. The literature often makes the assumption that firms in different sectors differ in their propensity to innovate but not in the drivers of innovation. The authors empirically assess whether this assumption is accurate through a series of econometric estimations and tests. Design/methodology/approach: The data used are derived from the Irish Community Innovation Survey 2004-2006. A series of multivariate probit models are estimated and the resulting coefficients are tested for parameter stability across sectors using likelihood ratio tests. Findings: The results indicate that there is a strong degree of heterogeneity in the drivers of innovation across sectors. The determinants of process, organisational, new to firm and new to market innovation varies across sectors suggesting that the pooling of sectors in an innovation production function may lead to biased inferences. Research limitations/implications: The implications of the results are that innovation policies targeted at stimulating innovation need to be tailored to particular industries. One size fits all policies would seem inappropriate given the large degree of heterogeneity observed across the drivers of innovation in different sectors. Originality/value: The value of this paper is that it provides an empirical test as to whether it is suitable to group sectoral data when estimating innovation production functions. Most papers simply include sectoral dummies, implying that only the propensity to innovate differs across sectors and that the slope of the coefficient estimates are in fact consistent across sectors.