Bioaerosol sampling by a personal rotating cup sampler CIP 10-M

High concentrations of bioaerosols containing bacterial, fungal and biotoxinic matter are encountered in many workplaces, e.g. solid waste treatment plants, waste water treatment plants and sewage networks. A personal bioaerosol sampler, the CIP 10-M (M-microbiologic), has been developed to measure worker exposure to airborne biological agents. This sampler is battery operated; it is light and easy to wear and offers full work shift autonomy. It can sample much higher concentrations than biological impactors and limits the mechanical stress on the microorganisms. Biological particles are collected in 2 ml of liquid medium inside a rotating cup fitted with radial vanes to maintain an air flow rate of 10 l min(-1) at a rotational speed of approximately 7,000 rpm. The rotating cup is made of sterilisable material. The sampled particles follow a helicoidal trajectory as they are pushed to the surface of the liquid by centrifugal force, which creates a thin vertical liquid layer. Sterile water or another collecting liquid can be used. Three particle size selectors allow health-related aerosol fractions to be sampled according to international conventions. The sampled microbiological particles can be easily recovered for counting, incubation or further biochemical analysis, e.g., for airborne endotoxins. Its physical sampling efficiency was laboratory tested and field trials were carried out in industrial waste management conditions. The results indicate satisfactory collection efficiency, whilst experimental application has demonstrated the usefulness of the CIP 10-M personal sampler for individual bioaerosol exposure monitoring.     

Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

Influence of community-based natural resource management strategies in the resilience of social-ecological systems

Different social-ecological systems around the world are managed under community-based natural resource management (CBNRM) strategies. This paper analyses how CBNRM strategies influence the resilience of social-ecological systems to the disturbances they face, drawing upon the experience of three Latin American cases (two in Mexico and one in Colombia). The cases differ in their CBNRM approach and in the time these governance systems have been in place. By using a mixed-method approach, we review the socio-ecological history and describe each CBNRM characteristics. We then assess their resilience to socioeconomic and environmental disturbances through a set of indicators. We found that CBNRM strategies influence positively and negatively resilience and that internal decisions might address important threats. On the positive side, the social-ecological systems with longer tradition of CBNRM and more local buy-in of commonly agreed objectives appear to be more resilient to environmental challenges. But, internal governance factors such as power imbalances, poor income distribution, and gender inequities linked to CBNRM undermine resilience and foster out migration. Finally, communities appear to have limited capacities to cope with external disturbances such as global drivers of change or national policies that negatively affect their social-ecological resilience.

     

Correction to: Influence of community-based natural resource management strategies in the resilience of social-ecological systems

Regional Environmental Change - The published online version contains mistake. Author name was incorrectly captured. Instead of Maria del Mar Delgado-Serrano was incorrectly captured as Ma del Mar...     

From mixed farming to intensive agriculture: energy profiles of agriculture in Quebec,Canada, 1871–2011

Regional Environmental Change - This article presents an energy analysis of Quebec agroecoystems at five periods of time: 1871, 1931, 1951, 1981, and 2011, calculating for each year the various...     

Trees on the move: using decision theory to compensate for climate change at the regional scale in forest social-ecological systems

Regional Environmental Change - The adaptation of social-ecological systems such as managed forests depends largely on decisions taken by forest managers who must choose among a wide range of...     

From vineyards to feedlots: a fund-flow scanning of sociometabolic transition in the Vallès County (Catalonia) 1860–1956–1999

Regional Environmental Change - We analyse the changes to agricultural metabolism in four municipalities of Vallès County (Catalonia, Iberia) by accounting for their agroecosystem funds and...     

Sustainability indicators in the swine industry of the Brazilian State of Santa Catarina

In recent decades, there has been a growing concern about measuring and evaluating the results of intensive production practices, such as the mode of integration practiced on a large scale by agro-industries. The present study discusses the application and the results of a Sustainability Indicators System in the context of the swine industry in the Brazilian State of Santa Catarina. These indicators, focused on the level of sustainability maturity, can be used as a way to diagnose and compare the efficiency of the industry from a broader perspective. The research findings indicate that most of the pig farms that have been studied can be classified as “in search of sustainability or sustainable.” Nevertheless, there are differences among the dimensions and between the most ranked farms and the others which must be considered for a better design and application of public policies and company strategies toward an effective and balanced social, economic and environmental sustainability.     

Environmental pollution in Africa

Mining and minerals industries are fast-growing, but at the same time, they have gained more attention due to their impacts over the environment and society. This research aims to provide new insights into the topic of perception and awareness toward sustainability in industrial mining in Brazil. The work included in-depth interviews with a set of companies’ managers/directors focusing in particular on aspects related to the social and environmental dimensions, including communication and relationship with the community, impact assessment and mitigation strategies. The knowledge and use of for formal indicators was also evaluated and analyzed through the proposed Model for Sustainability Assessment of Mining (SAoM model), which was applied to all participating companies. The results put in evidence the existing gap between large and small companies, with these last ones showing lower awareness for the impacts of their activities. The lack of community engagement and of local stakeholders’ involvement, as well as the disregard for actions to mitigate their environmental and social impacts, is the main challenges to be overcome by this sector. The sector has then a long path to go toward sustainability and an active involvement of public institutions is required to allow for its development without compromising locals welfare.