Analysis of Key Features of Non-Linear Behaviour Using Recurrence Quantification. Case Study: Urban Airborne Pollution at Mexico City

The use of recurrence plots have been extensively used in various fields. In this work, recurrence plots investigate the changes in the non-linear behaviour of urban air pollution using large datasets of raw data (hourly). This analysis has not been used before to extract information from large datasets for this type of non-linear problem. Two different approaches have been used to tackle this problem. The first approach is to show results according to monitoring network. The second approach is to show the results by particle type. This analysis shows the feasibility of using recurrence analysis for pollution monitoring and control.     

Microbial mediated arsenic biotransformation in wetlands

Arsenic (As) is a pervasive environmental toxin and carcinogenic metalloid. It ranks at the top of the US priority List of Hazardous Substances and causes worldwide human health problems. Wetlands, including natural and artificial ecosystems (i.e. paddy soils) are highly susceptible to As enrichment; acting not only as repositories for water but a host of other elemental/chemical moieties. While macroscale processes (physical and geological) supply As to wetlands, it is the micro-scale biogeochemistry that regulates the fluxes of As and other trace elements from the semi-terrestrial to neighboring plant/aquatic/atmospheric compartments. Among these fine-scale events, microbial mediated As biotransformations contribute most to the element’s changing forms, acting as the ‘switch’ in defining a wetland as either a source or sink of As. Much of our understanding of these important microbial catalyzed reactions follows relatively recent scientific discoveries. Here we document some of these key advances, with focuses on the implications that wetlands and their microbial mediated transformation pathways have on the global As cycle, the chemistries of microbial mediated As oxidation, reduction and methylation, and future research priorities areas.

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Development of a new risk-based framework to guide investment in water quality monitoring

An innovative framework for optimising investments in water quality monitoring has been developed for use by water and environmental agencies. By utilising historical data, investigating the accuracy of monitoring methods and considering the risk tolerance of the management agency, this new methodology calculates optimum water quality monitoring frequencies for individual water bodies. Such information can be applied to water quality constituents of concern in both engineered and natural water bodies and will guide the investment of monitoring resources. Here we present both the development of the framework itself and a proof of concept by applying it to the occurrence of hazardous cyanobacterial blooms in freshwater lakes. This application to existing data demonstrates the robustness of the approach and the capacity of the framework to optimise the allocation of both monitoring and mitigation resources. When applied to cyanobacterial blooms in the Swan Coastal Plain of Western Australia, we determined that optimising the monitoring regime at individual lakes could greatly alter the overall monitoring schedule for the region, rendering it more risk averse without increasing the amount of monitoring resources required. For water resources with high-density temporal data related to constituents of concern, a similar reduction in risk may be observed by applying the framework.     

A Multiple Criteria Decision Analysis Model Based on ELECTRE TRI-C for Erosion Risk Assessment in Agricultural Areas

This paper deals with a real-world decision-aiding problem for zoning the risk of erosion, total suspended solids emissions, and ecological consequences of their transfers towards the streams. One of these consequences is the decrease of fishes into the streams in agricultural watersheds, because of the clogging of spawning areas. Given the multiple criteria nature of the problem, the originality of our research is to adapt a new decision-aiding sorting method, ELECTRE TRI-C, for identifying risk zones in rural areas, where measures must be taken. The developed model was applied in a small watershed (Low Normandy, France) where the objective was to assess the most appropriate intervention for protecting the reproduction habitat of the salmonid fishes. Agricultural parcels were evaluated on multiple criteria for grouping them into four risk categories, which are related to risk levels as well as priorities on the improvement works. The decision-aiding sorting model is co-constructed, within a constructive approach, through an interaction process between decision-aiding analysts, environmental experts, and local actors for improving transparency and communication on the results. This model is linked with a geographical information system (GIS) for assessing a set of criteria and the visualization of the farming parcels along with their type of intervention they should be submitted to best practices. The assignment results were validated by the environmental experts. These results have a strong impact on the agricultural practices of the farmers into the watersheds. The model proposed in this paper can be considered as a useful decision aid tool in any regions for implementing public agricultural and environmental policies for protecting the ecological areas.     

Evaluating soil quality under a long-term integrated tillage–water–nutrient experiment with intensive rice–wheat rotation in a semi-arid Inceptisol,India

Long-term sustainability and a declining trend in productivity of rice–wheat rotation in the Indo-Gangetic plain, often direct towards the changes in soil quality parameters. Soil quality is decided through few sensitive soil physical, chemical and biological indicators as it cannot be measured directly. The present investigation was carried out to develop a valid soil quality index through some chosen indicators under long-term influences of tillage, water and nutrient-management practices in a rice–wheat cropping system. The experiment consisted of two tillage treatments, three irrigation treatments, and nine nutrient management treatments for both rice and wheat, was continued for 8 years. The index was developed using expert-opinion based conceptual framework model. After harvest of rice, the CFSQI-P (productivity) was higher under puddled situation, whereas CFSQI-EP (environmental protection) was more under non-puddled condition and 3-days of drainage was found promising for all the indices. No-tillage practice always showed higher soil quality index. The treatments either receiving full organics (100 % N) or 25 % substitution of fertilizer N with organics showed higher soil quality indices. Puddling, irrigation after 3 days of drainage and substitution of 25 % recommended fertilizer N dose with FYM in rice could be practiced for maintaining or enhancing soil quality. No-tillage, two irrigations, and domestic sewage sludge in wheat can safely be recommended for achieving higher soil quality.     

Biogenic polycyclic aromatic hydrocarbons in sediments of the San Joaquin River in California (USA), and current paradigms on their formation

Biogenic perylene and higher plant pentacyclic triterpenoid-derived alkylated and partially aromatized tetra- and pentacyclic derivatives of chrysene (3,4,7-trimethyl- and 3,3,7-trimethyl-1,2,3,4-tetrahydrochrysene, THC) and picene (1,2,9-trimethyl- and 2,2,9-trimethyl-1,2,3,4-tetrahydropicene, THP) were two- to four-fold more abundant than pyrogenic PAH in two sediment cores from the San Joaquin River in Northern California (USA). In a core from Venice Cut (VC), located in the river, PAH concentrations varied little downcore and the whole-core PAH concentration (biogenics?+?pyrogenics) was 250.6?±?73.7 ng g^?1 dw; biogenic PAH constituted 67?±?4 % of total PAH. THC were 26?±?9 % of total biogenic PAH, THP were 36?±?7 %, and perylene was 38?±?7 %. PAH distributions in a core from Franks Tract (FT), a former wetland that was converted to an agricultural tract in the late 1800s and flooded in 1938, were more variable. Surface sediments were dominated by pyrogenic PAH so that biogenic PAH were only ~30 % of total PAH. Deeper in the core, biogenic PAH constituted 60–93 % of total PAH; THC, THP and perylene were 31?±?28 %, 24?±?32 %, and 45?±?36 % of biogenic PAH. At 100–103 cm depth, THP constituted 80 % of biogenic PAH and at 120–123 cm perylene was 95 % of biogenic PAH. Current concepts related to precursors and transformation processes responsible for the diagenetic generation of perylene and triterpenoid-derived PAH are discussed. Distributions of biogenic PAH in VC and FT sediments suggest that they may not form diagenetically within these sediments but rather might be delivered pre-formed from the river’s watershed.     

Suitability of passive sampling for the monitoring of pharmaceuticals in Finnish surface waters

The occurrence of five pharmaceuticals, consisting of four anti-inflammatory and one antiepileptic drug, was studied by passive sampling and grab sampling in northern Lake Päijänne and River Vantaa. The passive sampling was performed by using Chemcatcher® sampler with a SDB-RPS Empore disk as a receiving phase. In Lake Päijänne, the sampling was conducted during summer 2013 at four locations near the discharge point of a wastewater treatment plant and in the years 2013 and 2015 at four locations along River Vantaa. The samples were analyzed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) in the multiple reaction monitoring mode. The concentrations of carbamazepine, diclofenac, ibuprofen, ketoprofen, and naproxen in Lake Päijänne determined by passive sampling ranged between 1.4–2.9 ng L^?1, 15–35 ng L^?1, 13–31 ng L^?1, 16–27 ng L^?1, and 3.3–32 ng L^?1, respectively. Similarly, the results in River Vantaa ranged between 1.2–40 ng L^?1, 15–65 ng L^?1, 13–33 ng L^?1, 16–31 ng L^?1, and 3.3–6.4 ng L^?1. The results suggest that the Chemcatcher passive samplers are suitable for detecting pharmaceuticals in lake and river waters.     

Coupling fishery dynamics,human health and social learning in a model of fish-borne pollution exposure

Pollution-induced illnesses are caused by toxicants that result from human activity and are often entirely preventable. However, where industrial priorities have undermined responsible governance, exposed populations must reduce their exposure by resorting to voluntary protective measures and demanding emissions abatement. This paper presents a coupled human–environment system model that represents the effects of water pollution on the health and livelihood of a fishing community. The model is motivated by an incident from 1949 to 1968 in Minamata, Japan, where methylmercury effluent from a local factory poisoned fish populations and humans who ate them. We model the critical role of risk perception in driving both social learning and the protective feedbacks against pollution exposure. These feedbacks are undermined in the presence of social misperceptions such as stigmatization of the injured. Through numerical simulation and scenario analysis, we compare our model results with historical datasets from Minamata, and find that the conditions for an ongoing pollution epidemic are highly unlikely without social misperception. We also find trade-offs between human health outcomes, the viability of the polluting industry and the survival of the fishery. We conclude that an understanding of human–environment interactions and misperception effects is highly relevant to the resolution of contemporary pollution problems, and merits further study.     

Connecting the dots: mapping habitat connectivity for tigers in central India

Large connected landscapes are paramount to maintain top predator populations. Across their range, tiger (Panthera tigris) populations occur in small fragmented patches of habitat, often isolated by large distances in human-dominated landscapes. We assessed connectivity between 16 protected areas (PAs) in central India, a global priority landscape for tiger conservation, using data on land use and land cover, human population density, and transportation infrastructure. We identified and prioritized movement routes using a combination of least-cost corridor modeling and circuit theory. Our analyses suggest that there are several opportunities to maintain connectivity in this landscape. We mapped a total of thirty-five linkages in the region and calculated metrics to estimate their quality and importance. The highest quality linkages as measured by the ratio of cost-weighted distance to Euclidean distance are Kanha–Phen/Bandhavgarh–SanjayGhasidas/Melghat–Satpura, and cost-weighted distance to least-cost path length are Nawegaon–Tadoba/Achanakmar–SanjayGhasidas/Kanha–Phen. We used current flow centrality to evaluate the contribution of each PA and linkage toward facilitating animal movement. Values are highest for Kanha and Pench tiger reserves, and the linkages between Kanha–Phen, Kanha–Pench, and Pench–Satpura, suggesting that these PAs and linkages play a critical role in maintaining connectivity in central India. In addition, smaller areas such as Bor, Nawegaon, and Phen have high centrality scores relative to their areas and thus may act as important stepping stones. We mapped pinch points, which are sections of the linkages where tiger movement is restricted due to unfavorable habitat, transportation networks, human habitation, or a combination of factors. Currently, very limited data exist on tiger movement outside of PAs to validate model results. Regional-scale connectivity mapping efforts can assist managers and policy makers to develop strategic plans for balancing wildlife conservation and other land uses in the landscape.     

A new approach for the modelling of chestnut wood photo-degradation monitored by different spectroscopic techniques

The aim of this work is to study the colour and chemical modifications of the surfaces in chestnut wood samples as a consequence of irradiating in a controlled environment. The changes were investigated by a new analytical approach by combining traditional techniques such as reflectance spectrophotometry in the visible range and Fourier transform infrared spectroscopy with new hyperspectral imaging, in order to obtain forecast models to describe the phenomenon. The statistical elaboration of the experimental data allowed to validate the measurements and to obtain models enabling to relate the investigated parameters; the elaboration of the hyperspectral images by chemometric methods allowed for studying the changes in the reflectance spectra. A result of great importance is the possibility to correlate the oxidation of wood chemical components with the colour change in a totally non-invasive modality. This result is particularly relevant in the field of cultural heritage and in general in the control processes of wooden materials.