The role of digital data entry in participatory environmental monitoring

Many argue that monitoring conducted exclusively by scientists is insufficient to address ongoing environmental challenges. One solution entails the use of mobile digital devices in participatory monitoring (PM) programs. But how digital data entry affects programs with varying levels of stakeholder participation, from nonscientists collecting field data to nonscientists administering every step of a monitoring program, remains unclear. We reviewed the successes, in terms of management interventions and sustainability, of 107 monitoring programs described in the literature (hereafter programs) and compared these with case studies from our PM experiences in Australia, Canada, Ethiopia, Ghana, Greenland, and Vietnam (hereafter cases). Our literature review showed that participatory programs were less likely to use digital devices, and 2 of our 3 more participatory cases were also slow to adopt digital data entry. Programs that were participatory and used digital devices were more likely to report management actions, which was consistent with cases in Ethiopia, Greenland, and Australia. Programs engaging volunteers were more frequently reported as ongoing, but those involving digital data entry were less often sustained when data collectors were volunteers. For the Vietnamese and Canadian cases, sustainability was undermined by a mismatch in stakeholder objectives. In the Ghanaian case, complex field protocols diminished monitoring sustainability. Innovative technologies attract interest, but the foundation of effective participatory adaptive monitoring depends more on collaboratively defined questions, objectives, conceptual models, and monitoring approaches. When this foundation is built through effective partnerships, digital data entry can enable the collection of more data of higher quality. Without this foundation, or when implemented ineffectively or unnecessarily, digital data entry can be an additional expense that distracts from core monitoring objectives and undermines project sustainability. The appropriate role of digital data entry in PM likely depends more on the context in which it is used and less on the technology itself.     

Chitosan-polypropylene imine dendrimer hybrid: a new ecological biomordant for cochineal dyeing of wool

The classical use of synthetic dyes is causing issues of environmental pollution and heath risk. As a consequence natural dyes are gaining interest, but the use of natural dyes still includes toxic reagents such as metals as mordants and acids to enhance color and yield. Therefore, we designed a new chitosan-polypropylene imine dendrimer hybrid at 0–2000 mg/L to treat wool before dyeing with cochineal. We compared dye exhaustion, color depth, color characteristics, and color fastness of the new process with dyed pristine and metal mordanted wool. Results show that wool pretreatment improved dye exhaustion from 48 to 88 %, shifted saturation point toward lower dye concentration from 3000 to 1000 mg/L, and improved color depth from 13.68 for pristine wool and 15.17 for metal mordanted wool to 23.89 for the new process.     

International Environmental Agreements: Design of Optimal Transfers Under Heterogeneity

International environmental agreements (IEAs) can coordinate abatement of transboundary pollutants. This paper investigates how heterogeneous countries facing a stock pollutant might structure such an agreement. In particular, we examine how an IEA might be implemented with a set of monetary transfers. The focus is on transfers that are time invariant, linear in emissions, and consistent with budget balance. There is a range of such schemes that would induce efficient emissions. We provide a simple and intuitive characterization of these penalties and describe how specific proposals might be chosen in order to facilitate compliance and implementation. Our proposals are illustrated with a simple example. We show that heterogeneity reduces the scope for penalty schemes to jointly satisfy desirable properties.     

Analytical survey of arsenic in geothermal waters from sites in Kyushu,Japan, and a method for removing arsenic using magnetite

The objective of this study was to survey the cation and anion contents of geothermal waters to gather fundamental information on geographical variations. Sixteen sites in hot spring areas on the island of Kyushu in Japan were studied. The study focused on the arsenic content of the samples. Very high arsenic concentrations (more than 0.1 mg/l) were detected in most of the geothermal waters sampled. High contents of boron and fluoride (more than 1.0 mg/l) were also detected in some samples. Arsenic removal was performed on a laboratory scale using columns packed with a magnetite-type adsorbent. The reduction of arsenic contamination to a concentration of less than 0.01 mg/l could be achieved in the early stages of adsorption (bed volume = 200).     

The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River,Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.     

The importance of monitoring and evaluation in adaptive maritime spatial planning

Adaptive maritime spatial planning (MSP) uses monitoring and evaluation of the effectiveness of spatial and temporal management measures to promote understanding and improve planning and decision-making. An adaptive approach to MSP involves exploring alternative ways to meet management objectives, predicting the outcomes of alternative management measures, implementing one or more of these alternative management measures, monitoring to learn about the effects of management measures, and then using the results to update knowledge and adjust management actions. A monitoring and evaluation plan should be designed to be both cost effective and comprehensive. The process of setting and assessing performance metrics requires that the ecological and socio-economic objectives of the spatial management plan must be clearly stated up front for management actions to reflect those objectives accurately. To evaluate the effectiveness of a MSP plan, a range of ecological, socio-economic and institutional indicators need to be developed and monitored.     

Modelling short-term effects of ozone on morbidity: an application to the city of Milano,Italy, 1995–2003

In this paper, we explore a range of concerns that arise in measuring short-term effects of ozone on health. In particular, we tackle the problem of measuring exposure using alternative daily measures of ozone derived from hourly concentrations. We adopt the exposure paradigm of Chiogna and Bellini (Environmetrics 13:55–69, 2002) extending it to ozone concentrations, and we compare its performances with respect to traditional exposure measures by exploiting model selection. To investigate the stability of model selection, we then apply the idea of bootstrapping the modelling process.