Parts-per-trillion LC-MS(Q) analysis of herbicides and transformation products in surface water

The goal of this study was to develop a robust method of analyzing surface water samples for S-triazine herbicides, chloroacetanilide herbicides, and their transformation products (TPs) using solid-phase extraction (SPE) followed by liquid chromatograph-mass spectrometry (LC-MS) with electrospray ionization (ESI) by in-source collision-induced dissociation (ISCID) capability of an orthogonal electrospray ionization probe on a single quadrupole LC-MS system. The method developed here met the goals of the study and yielded estimated method detection limits (EMDLs) averaging 0.3 ± 0.1 ng L(-1) for S-triazines and their TPs and 0.7 ± 0.4 ng L(-1) for chloroacetanilides and TPs. Spiked filtered river water yielded SPE recoveries ranging from 94.2 % ± 4.8 % for S-triazines and TPs after eliminating three compounds with less that 65 % recovery from analysis and 95.9 % ± 19 % for chloroacetanilides and their TPs. The method was field-tested with filtered water samples collected from four sites over a four-month period. Detectible values of S-triazines and TPs ranged from 0.3 to 1540 ng L(-1) with a mean of 79.3 and a median of 19.4 ng L(-1). Detectible values for chloroacetanilides and TPs ranged from 0.31 to 3780 ng L(-1) with a mean of 252 and a median of 25.6 ng L(-1). An additional goal was to determine if the method was useful for microbial degradation studies using native bacterial communities. The bacteria transformed atrazine (2-chloro-4-ethylamino-6-isopropylamino-S-triazine) solely into 2-hydroxy atrazine (2-hydroxy-4-ethylamino-6-isopropylamino-S-triazine) with concentrations of 78.4, 63.3 and 32.5 ng L(-1) after 12 days of incubation compared with 6.3 and 7.1 ng L(-1) for control dark and control sunlight respectively.     

Looking beyond the average agricultural impacts in defining adaptation needs in Europe

The effects of climate change on agriculture are often characterised by changes in the average productivity of crops; however, these indicators provide limited information regarding the risks associated with fluctuations in productivity resulting from future changes in climate variability that may also affect agriculture. In this context, this study evaluates the combined effects of the risks associated with anomalies reflected by changes in the mean crop yield and the variability of productivity in European agro-climatic regions under future climate change scenarios. The objective of this study is to evaluate adaptation needs and to identify regional effects that should be addressed with greater urgency in the light of the risks and opportunities that are identified. The results show differential effects on regional agriculture and highlight the importance of considering both regional average impacts and the variability in crop productivity in setting priorities for the adaptation and maintenance of rural incomes and agricultural insurance programmes.     

Building resilience to water scarcity in southern Spain: a case study of rice farming in Doñana protected wetlands

Agricultural water management needs to evolve in view of increased water scarcity, especially when farming and natural protected areas are closely linked. In the study site of Doñana (southern Spain), water is shared by rice producers and a world heritage biodiversity ecosystem. Our aim is to contribute to defining adaptation strategies that may build resilience to increasing water scarcity and minimize water conflicts among agricultural and natural systems. The analytical framework links a participatory process with quantitative methods to prioritize the adaptation options. Bottom-up proposed adaptation measures are evaluated by a multi-criteria analysis (MCA) that includes both socioeconomic criteria and criteria of the ecosystem services affected by the adaptation options. Criteria weights are estimated by three different methods—analytic hierarchy process, Likert scale and equal weights—that are then compared. Finally, scores from an MCA are input into an optimization model used to determine the optimal land-use distribution in order to maximize utility and land-use diversification according to different scenarios of funds and water availability. While our results show a spectrum of perceptions of priorities among stakeholders, there is one overriding theme that is to define a way to restore part of the rice fields to natural wetlands. These results hold true under the current climate scenario and even more so under an increased water scarcity scenario.     

Adaptation options for marine industries and coastal communities using community structure and dynamics

Identifying effective adaptation strategies for coastal communities dependent on marine resources and impacted by climate change can be difficult due to the dynamic nature of marine ecosystems. The task is more difficult if current and predicted shifts in social and economic trends are considered. Information about social and economic change is often limited to qualitative data. A combination of qualitative and quantitative models provide the flexibility to allow the assessment of current and future ecological and socio-economic risks and can provide information on alternative adaptations. Here, we demonstrate how stakeholder input, qualitative models and Bayesian belief networks (BBNs) can provide semi-quantitative predictions, including uncertainty levels, for the assessment of climate and non-climate-driven change in a case study community. Issues are identified, including the need to increase the capacity of the community to cope with change. Adaptation strategies are identified that alter positive feedback cycles contributing to a continued decline in population, local employment and retail spending. For instance, the diversification of employment opportunities and the attraction of new residents of different ages would be beneficial in preventing further population decline. Some impacts of climate change can be combated through recreational bag or size limits and monitoring of popular range-shifted species that are currently unmanaged, to reduce the potential for excessive removal. Our results also demonstrate that combining BBNs and qualitative models can assist with the effective communication of information between stakeholders and researchers. Furthermore, the combination of techniques provides a dynamic, learning-based, semi-quantitative approach for the assessment of climate and socio-economic impacts and the identification of potential adaptation strategies.     

Determinants of household fuel choices among Nigerian family heads: are there gender-differentiated impacts?

The consensus in the literature holds that female-headed households (FHHs) are more vulnerable to social and economic exclusion than male-headed households (MHHs). This paper investigates the socioeconomic determinants of household cooking fuel choices across MHHs and FHHs, using the rich Nigerian Demographic Health Survey data. Using the exogenous switching treatment effect regression (ESTER) technique, the study is able to unravel differences in socioeconomic effects of gender inequality on cooking fuel choices in Nigeria. The results validate the energy ladder hypothesis in the Nigerian case and show that the choices of dirty fuel (biomass) is more prevalent among the de-jure FHH when compared with the de-facto FHH and MHHs. Also, the probability of biomass-use among MHHs would have fallen by 1.3% if MHHs had similar socioeconomic attributes as the FHHs. In the same vain for FHHs, the probability of kerosene-use would have increased by 2%. The study observed no gender gap in kerosene-use. Thus, the established gender gap in biomass- and kerosene-use would have reduced to 6.7% and 2.8%, respectively, if the de-facto FHHs had same socioeconomic attributes as the de-jures. Considering the traditional gendered household division of labor within the households, de-jure FHHs’ energy choices may be due to limited economic opportunities that guarantees cleaner energy options.

     

Environmental PCB forensics: processes and issues

Environmental Science and Pollution Research - PCB forensic science is the process of identifying the source(s) of polychlorinated biphenyls (PCBs) at a site in the context of a legal proceeding to...     

Susceptibility of different yeast species to environmental toxic metals

The purpose of the study reported here was to investigate the relative resistance of yeast species to various metallic and metalloid ions, with a view to gaining more knowledge on this subject, as resistant species may become dominant in habitats contaminated with the relevant metals. Saccharomyces cerevisiae, Candida albicans and Candida tropicalis were grown in media containing different concentrations of mercury (as HgCl(2)), cadmium (as CdCl(2)), lead (as Pb(CH(3)COO)(2)), arsenic (as Na(2)HAsO(4)) and selenium (as Na(2)SeO(3)) for various intervals. Invariably, the two Candida species turned out to be more resistant to all the metals studied than S. cerevisiae. The metal showing the highest toxicity for these species was mercury, with cadmium being the second, lead, the third and arsenic and selenium being the least toxic elements. Strains showing resistance to mercury were isolated, even in the case of S. cerevisiae.