Ecosystem responses to climate change at a Low Arctic and a High Arctic long-term research site

Long-term measurements of ecological effects of warming are often not statistically significant because of annual variability or signal noise. These are reduced in indicators that filter or reduce the noise around the signal and allow effects of climate warming to emerge. In this way, certain indicators act as medium pass filters integrating the signal over years-to-decades. In the Alaskan Arctic, the 25-year record of warming of air temperature revealed no significant trend, yet environmental and ecological changes prove that warming is affecting the ecosystem. The useful indicators are deep permafrost temperatures, vegetation and shrub biomass, satellite measures of canopy reflectance (NDVI), and chemical measures of soil weathering. In contrast, the 18-year record in the Greenland Arctic revealed an extremely high summer air-warming of 1.3 °C/decade; the cover of some plant species increased while the cover of others decreased. Useful indicators of change are NDVI and the active layer thickness.     

When experts disagree: the need to rethink indicator selection for assessing sustainability of agriculture

Sustainability indicators are well recognized for their potential to assess and monitor sustainable development of agricultural systems. A large number of indicators are proposed in various sustainability assessment frameworks, which raises concerns regarding the validity of approaches, usefulness and trust in such frameworks. Selecting indicators requires transparent and well-defined procedures to ensure the relevance and validity of sustainability assessments. The objective of this study, therefore, was to determine whether experts agree on which criteria are most important in the selection of indicators and indicator sets for robust sustainability assessments. Two groups of experts (Temperate Agriculture Research Network and New Zealand Sustainability Dashboard) were asked to rank the relative importance of eleven criteria for selecting individual indicators and of nine criteria for balancing a collective set of indicators. Both ranking surveys reveal a startling lack of consensus amongst experts about how best to measure agricultural sustainability and call for a radical rethink about how complementary approaches to sustainability assessments are used alongside each other to ensure a plurality of views and maximum collaboration and trust amongst stakeholders. To improve the transparency, relevance and robustness of sustainable assessments, the context of the sustainability assessment, including prioritizations of selection criteria for indicator selection, must be accounted for. A collaborative design process will enhance the acceptance of diverse values and prioritizations embedded in sustainability assessments. The process by which indicators and sustainability frameworks are established may be a much more important determinant of their success than the final shape of the assessment tools. Such an emphasis on process would make assessments more transparent, transformative and enduring.     

Overview of surface measurements and spatial characterization of submicrometer particulate matter during the DISCOVER-AQ 2013 campaign in Houston,TX

The sources of submicrometer particulate matter (PM₁) remain poorly characterized in the industrialized city of Houston, TX. A mobile sampling approach was used to characterize PM₁ composition and concentration across Houston based on high-time-resolution measurements of nonrefractory PM₁ and trace gases during the DISCOVER-AQ Texas 2013 campaign. Two pollution zones with marked differences in PM₁ levels, character, and dynamics were established based on cluster analysis of organic aerosol mass loadings sampled at 16 sites. The highest PM₁ mass concentrations (average 11.6 ± 5.7 µg/m³) were observed to the northwest of Houston (zone 1), dominated by secondary organic aerosol (SOA) mass likely driven by nighttime biogenic organonitrate formation. Zone 2, an industrial/urban area south/east of Houston, exhibited lower concentrations of PM₁ (average 4.4 ± 3.3 µg/m³), significant organic aerosol (OA) aging, and evidence of primary sulfate emissions. Diurnal patterns and backward-trajectory analyses enable the classification of airmass clusters characterized by distinct PM sources: biogenic SOA, photochemical aged SOA, and primary sulfate emissions from the Houston Ship Channel. Principal component analysis (PCA) indicates that secondary biogenic organonitrates primarily related with monoterpenes are predominant in zone 1 (accounting for 34% of the variability in the data set). The relevance of photochemical processes and industrial and traffic emission sources in zone 2 also is highlighted by PCA, which identifies three factors related with these processes/sources (~50% of the aerosol/trace gas concentration variability). PCA reveals a relatively minor contribution of isoprene to SOA formation in zone 1 and the absence of isoprene-derived aerosol in zone 2. The relevance of industrial amine emissions and the likely contribution of chloride-displaced sea salt aerosol to the observed variability in pollution levels in zone 2 also are captured by PCA.

Implications: This article describes an urban-scale mobile study to characterize spatial variations in submicrometer particulate matter (PM₁) in greater Houston. The data set indicates substantial spatial variations in PM₁ sources/chemistry and elucidates the importance of photochemistry and nighttime oxidant chemistry in producing secondary PM₁. These results emphasize the potential benefits of effective control strategies throughout the region, not only to reduce primary emissions of PM₁ from automobiles and industry but also to reduce the emissions of important secondary PM₁ precursors, including sulfur oxides, nitrogen oxides, ammonia, and volatile organic compounds. Such efforts also could aid in efforts to reduce mixing ratios of ozone.     

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.