Moral reasoning in adaptation to climate change

Moral foundations theory argues that moral reasoning is widely observed and fundamental to the legitimacy of relevant governance and policy interventions. A new analytical framework to examine and test how moral reasoning underpins and legitimizes governance and practice on adaptation to climate change risks is proposed. It develops a typology of eight categories of vulnerability-based and system-based moral reasoning that pertain to the dilemmas around adaptation and examines the prevalence of these moral categories in public discourse about specific adaptation issues. The framework is tested using data on climate change impact, adaptation, and societal responsibility, drawn from 14 focus groups comprising 148 participants across the UK. Participants consistently use moral reasoning to explain their views on climate adaptation; these include both vulnerability-based and system-based framings. These findings explain public responses to adaptation options and governance, and have implications for the direction of adaptation policy, including understanding which types of reasoning support politically legitimate interventions.     

Vetoing the future: political constraints and renewable energy

Despite the increased importance of and attention to renewable energy, its share in the overall energy mix has varied significantly across countries and over time. There are many determinants of clean energy transitions; this study focuses on political constraints. Here it is argued that political systems that have fewer political constraints have fewer access points through which powerful status quo veto players can slow the progress of clean energy reforms. To test the theory, a hierarchical model is applied on a dataset of 125 countries over four decades. The results provide significant support for the theory. Furthermore, the effects for political constraints hold even when we distinguish between hydro and non-hydro renewable sources and control for regime type. This study builds on research that recognizes the importance of politics in understanding the challenges and opportunities of clean energy reform.     

Health risk assessment of potentially harmful elements and dietary minerals from vegetables irrigated with untreated wastewater,Pakistan

In the developing world, vegetables are commonly grown in suburban areas irrigated with untreated wastewater containing potentially harmful elements (PHEs). In Pakistan, there is no published work on the bioaccessibility aspect of PHEs and dietary minerals (DMs) in sewage-irrigated soil or the vegetables grown on such soils in Pakistan. Several industrial districts of Pakistan were selected for assessment of the risk associated with the ingestion of vegetables grown over sewage-irrigated soils. Both the total and bioaccessible fraction of PHEs (Cd, Co, Cr, Ni, and Pb) and DMs (Fe, Cu, Mn, Zn, Ca, Mg, and I) in soils and vegetable samples were measured. The concentrations of these PHEs and DMs in sewage-irrigated and control soils were below published upper threshold limits. However, compared to control soils, sewage irrigation over the years decreased soil pH (7.7 vs 8.1) and enhanced dissolved organic carbon (1.8 vs 0.8 %), which could enhance the phyto-availability of PHEs and DMs to crops. Of the PHEs and DMs, the highest transfer factor (soil to plant) was noted for Cd and Ca, respectively. Concentrations of PHEs in most of the sewage-irrigated vegetables were below the published upper threshold limits, except for Cd in the fruiting portion of eggplant and bell pepper (0.06–0.08 mg/kg Cd, dry weight) at three locations in Gujarat and Kasur districts. The bioaccessible fraction of PHEs can reduce the context of dietary intake measurements compared to total concentrations, but differences between both measurements were not significant for Cd. Since the soils of the sampled districts are not overly contaminated compared to control sites, vegetables grown over sewage-irrigated soils would provide an opportunity to harvest mineral-rich vegetables potentially providing consumers 62, 60, 12, 104, and 63 % higher dietary intake of Cu, Mn, Zn, Ca, and Mg, respectively. Based on Fe and vanadium correlations in vegetables, it is inferred that a significant proportion of total dietary Fe intake could be contributed by soil particles adhered to the consumable portion of vegetables. Faecal sterol ratios were used to identify and distinguish the source of faecal contamination in soils from Gujranwala, Gujarat, and Lahore districts, confirming the presence of human-derived sewage biomarkers at different stages of environmental alteration. A strong correlation of some metals with soil organic matter concentration was observed, but none with sewage biomarkers.     

Metal-contaminated potato crops and potential human health risk in Bolivian mining highlands

This study assessed metals in irrigation water, soil and potato crops impacted by mining discharges, as well as potential human health risk in the high desert near the historic mining center of Potosí, Bolivia. Metal concentrations were compared with international concentration limit guidelines. In addition, an ingested average daily dose and minimum risk level were used to determine the hazard quotient from potato consumption for adults and children. Irrigation water maximum concentrations of Cd, Pb and Zn in mining-impacted sites were elevated 20- to 1100-fold above international concentration limit guidelines. Agricultural soils contained total metal concentrations of As, Cd, Pb and Zn that exceeded concentration limits in agricultural soil guidelines by 22-, 9-, 3- and 12-fold, respectively. Potato tubers in mining-impacted sites had maximum concentrations of As, Cd, Pb and Zn that exceeded concentration limits in commercially sold vegetables by 9-, 10-, 16- and fourfold, respectively. Using conservative assumptions, hazard quotients (HQ) for potatoes alone were elevated for As, Cd and Pb among children (range 1.1–71.8), in nearly all of the mining-impacted areas; and for As and Cd among adults (range 1.2–34.2) in nearly all of the mining-impacted areas. Only one mining-impacted area had a Pb adult HQ for potatoes above 1 for adults. Toxic trace elements in a major regional dietary staple may be a greater concern than previously appreciated. Considering the multitude of other metal exposure routes in this region, it is likely that total HQ values for these metals may be substantially higher than our estimates.     

Atrazine contamination in agricultural soils from the Yangtze River Delta of China and associated health risks

Atrazine is one of the most widely applied and persistent herbicides in the world. In view of limited information on the regional contamination of atrazine in soils in China, this study investigated the spatial distribution and environmental impacts of atrazine in agricultural soils collected from the Yangtze River Delta (YRD) as an illustrative analysis of rapidly developing regions in the country. The results showed that the concentrations of atrazine in the YRD agricultural soils ranged from <1.0 to 113 ng/g dry weight, with a mean of 5.7 ng/g, and a detection rate of 57.7 % in soils. Pesticide factory might be a major source for the elevated levels of atrazine in Zhejiang Province. The contamination of atrazine was closely associated with land use types. The concentrations and detection rates of atrazine were higher in corn fields and mulberry fields than in rice paddy fields. There was no significant difference in compositions of soil microbial phospholipids fatty acids among the areas with different atrazine levels. Positive relationship (R = 0.417, p < 0.05, n = 30) was observed between atrazine and total microbial biomass. However, other factors, such as soil type and land management practice, might have stronger influences on soil microbial communities. Human health risks via exposure to atrazine in soils were estimated according to the methods recommended by the US EPA. Atrazine by itself in all the soil samples imposed very low carcinogenic risks (<10^?6) and minimal non-cancer risks (hazard index <1) to adults and children.     

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

How Good? Ethical Criteria for a ‘Good Life’ for Farm Animals

The Farm Animal Welfare Council’s concept of a Good Life gives an idea of an animal’s quality of life that is over and above that of a mere life worth living. The concept needs explanation and clarification, in order to be meaningful, particularly for consumers who purchase farm animal produce. The concept could allow assurance schemes to apply the label to assessments of both the potential of each method of production, conceptualised in ways expected to enhance consumers’ engagement such as ‘naturalness’ and ‘freedom’; and the concept of a life worth living as a safeguard threshold below which no animal’s actual welfare should fall, based on each animal’s overall affective states. This may provide a framework for development of the Good Life concept, within scientific and sociological fields, in order to allow reliable and influential use by assessors, consumers and retailers.