Trends and variations of pH and hardness in a typical semi-arid river in a monsoon climate region during 1985–2009

The rapid growth of urbanization and industrialization, along with dramatic climate change, has strongly influenced hydrochemical characteristics in recent decades in China and thus could cause the variation of pH and general total hardness of a river. To explore such variations and their potential influencing factors in a river of the monsoon climate region, we analyzed a long-term monitoring dataset of pH, SO₄ ^2?, NO_x, general total hardness (GH), Mg²⁺, Ca²⁺, and Cl^? in surface water and groundwater in the Luan River basin from 1985 to 2009. The nonparametric Seasonal Kendall trend test was used to test the long-term trends of pH and GH. Relationship between the affecting factors, pH and GH were discussed. Results showed that pH showed a decreasing trend and that GH had an increasing trend in the long-term. Seasonal variation of pH and GH was mainly due to the typical monsoon climate. Results of correlation analysis showed that the unit area usage amounts of chemical fertilizer, NO₃ ^?, and SO₄ ^2? were negatively correlated with pH in groundwater. In addition, mining activity affected GH spatial variation. Acid deposition, drought, and increasing the use of chemical fertilizers would contribute to the acidification trend, and mining activities would affect the spatial variation of GH. Variations of precipitation and runoff in semi-arid monsoon climate areas had significant influences on the pH and GH. Our findings implied that human activities played a critical role in river acidification in the semi-arid monsoon climate region of northern China.     

Dry reforming of methane to syngas: a potential alternative process for value added chemicals—a techno-economic perspective

During the past decade, there has been increasing global concern over the rise of anthropogenic CO₂ emission into the Earth’s atmosphere (J Air Waste Manage Assoc 53:645–715, 2003). The utilization of CO₂ to produce any valuable product is need of the hour. The production of syngas from CO₂ and CH₄ seems to be one of the promising alternatives in terms of industrial utilization, as it offers several advantages: (a) mitigation of CO₂, (b) transformation of natural gas and CO₂ into valuable syngas, and (c) producing syngas with H₂/CO ratio 1 which may further be used for the production of valuable petrochemicals (J Air Waste Manage Assoc 53:645–715, 2003). A conceptual design for the production of synthesis gas by dry reforming of methane is presented here. An economic assessment of this process with an integrated methanol production section as a case was conceptualized and compared with the conventional steam methane reforming route to produce methanol. The economic study indicated that dry reforming of natural gas/methane is a competitive process with lower operating and capital costs in comparison with steam reforming assuming negligible cost of CO₂ import.     

Wastewater reuse: modeling chloroform formation

The chloroform is a substance that presents a significant risk to or via the aquatic environment. Thus, the emissions, discharges and losses of this substance need to be controlled during wastewater disinfection for reclamation and reuse purposes. Due to its carcinogenetic potential, multiple studies have been carried out on drinking and surface/natural waters but less consideration has been directed to the wastewater disinfection. The focus of this work studied the formation of chloroform during chlorination in prepared waters or artificial matrices that intended to simulate wastewaters stored in landscape ponds for green areas irrigation. The relation between reaction time, chlorine dose, and chloroform formation and the variation of the dissolved organic carbon (DOC) content during the reaction was assessed. A two-variant model was proposed to simulate breakpoint chlorination practices (when chlorine dose is equal or lower than chlorine demand) and super chlorination techniques (when chlorine dose tends to surpass chlorine demand). The model was validated by the application of actual data from working conditions of six wastewater treatment plants located in Algarve, Portugal, including other data obtained in previous research studies that were not used in the model development, and by comparing the predicted values with real measured ones.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Increasing CACNA1C expression in placenta containing high Cd level: an implication of Cd toxicity

Cadmium (Cd) has known to produce many adverse effects on organs including placenta. Many essential transporters are involved in Cd transport pathways such as DMT-1, ZIP as well as L-VDCC. Fourteen pregnant women participated and were divided into two groups: high and low Cd-exposed (H-Cd, L-Cd) groups on the basis of their residential areas, Cd concentrations in the blood (B-Cd), urine (U-Cd), and placenta (P-Cd). The results showed that the B-Cd and U-Cd were significantly increased in H-Cd group (p < 0.05). Interestingly, the P-Cd in H-Cd group was elevated (p < 0.05) and positively related to their B-Cd and U-Cd values (p < 0.05). However, the mean cord blood Cd (C-Cd) concentration in H-Cd group was not significantly increased about 2.5-fold when comparing to L-Cd group. To determine the Cd accumulation in placental tissues, metallothionein-1A (MT-1A) and metallothionein-2A (MT-2A) expressions were used as biomarkers. The results revealed that mean MT-1A and MT-2A mRNAs and MT-1/2 proteins were up-regulated in H-Cd group (p < 0.05). In addition, the Ca channel alpha 1C (CACNA1C) mRNA and protein expressions were noticeably elevated in H-Cd group (p < 0.05). From these findings, we suggested that CACNA1C might be implicated in Cd transport in human placenta.     

Assessing the vulnerability of rare plants using climate change velocity,habitat connectivity,and dispersal ability: a case study in Alberta,Canada

Climate change generally requires species to migrate northward or to higher elevation to maintain constant climate conditions, but migration requirement and migration capacity of individual species can vary greatly. Individual populations of species occupy different positions in the landscape that determine their required range shift to maintain similar climate, and likewise the migration capacity depends on habitat connectivity. Here, we demonstrate an approach to quantifying species vulnerabilities to climate change for 419 rare vascular plants in Alberta, Canada, based on a multivariate velocity of climate change metric, local habitat fragmentation, and migration capacity. Climate change velocities indicated that future migration requirements ranged from 1 to 5 km/year in topographically complex landscapes, such as the Alberta Foothills and Rocky Mountains. In contrast, migration requirements to maintain constant climate in relatively flat Boreal Plains, Parkland, and Grassland ranged from 4 to 8 km/year. Habitat fragmentation was also highest in these flat regions, particularly the Parkland Natural Region. Of the 419 rare vascular plants assessed, 36 were globally threatened (G1–G3 ranking). Three globally threatened species were ranked as extremely vulnerable and five species as highly vulnerable to the interactions among climate change velocity, habitat fragmentation, and migration capacity. Incorporating dispersal characteristics and habitat fragmentation with local patterns in climate change velocity improves the assessment of climate change threats to species and may be applied to guide monitoring efforts or conservation actions.     

Institutional challenges of adopting ecosystem-based adaptation to climate change

In view of past environmental degradation and anticipated climate change impacts, we assessed the potential for ecosystem-based adaptation in the Murray-Darling Basin, Australia. In a workshop with staff from three Catchment Management Authorities (CMAs) who had jurisdiction over three sub-basins, as well as technical experts, nine adaptation options were identified that ranged from environmental flows, restoring river channel habitat, reoperating infrastructure and controlling invasive species. A Catchment Adaptation Framework was developed and used to assess and compare these adaptation options with each of the CMAs, drawing on interviews with their key stakeholders, to identify the risks, benefits and costs. We found that ecosystem-based adaptation can augment catchment management programs and requires investment in a suite of different but complementary measures to lower risk. Our research found institutional challenges in implementing this approach, including the complexities of multi-agency management, constricting legal requirements, narrow funding arrangements, under-developed institutional capacity, difficulties of implementing catchment-scale programs on private property and the need to adhere to community expectations. These institutional issues are ubiquitous internationally and point to the wider issues of providing sufficient management capacity to support adaptation. The Catchment Adaptation Framework presented here enables river basin managers to systematically assess the adaptation options to better inform their decision-making.     

Recent sediment accumulation rates in contrasting lakes in the Carpathians (Romania): impacts of shifts in socio-economic regime

Longer-term environmental studies are increasingly used to better understand contemporary ecosystems conditions and for forecasting their future trajectories. Here, we use radiometric measurements and the characterisation of sediment properties from six mountain and a lowland lake in Central Eastern Europe with the aim to assess temporal and spatial variability in sediment accumulation rates (SARs) in relation to three socio-economic regimes: traditional (1840–1948), socialist (1948–1989) and post-socialist (post-1990). We also set out to determine reference conditions for these lakes i.e. conditions before significant human impact. Our results show a trend of increasing SARs from basal sediments (pre 1840) towards the present at only two sites. This contrasts with findings from Western and Central European lakes where SARs have predominantly increased from 1850 towards the top of cores. We highlight the differential impacts of the traditional, socialist and post-socialist periods on the SARs at these lakes. Lowland and mid-elevations lakes (n = 2) were most markedly impacted by the socialist period of land use regime; lakes from the southern Carpathians (n = 2) were more impacted in the traditional period (transhumance pastoral activities), whereas those from the north (n = 3) in the socialist and post-socialist periods (summer pastoralism). Results from our study show a continuous anthropogenic impact during the entire period considered, even in remote mountain areas. This suggests that a temporal frame of 100–150 years is too short to meaningfully register the reference conditions of these lakes. Furthermore, a predominantly natural state may not have existed for centuries in this region.     

Household preferences and willingness to pay (WTP) for freshwater quality improvement in Pakistan’s Swat River Valley

This two-part study investigates household preferences and willingness to pay (WTP) for water quality improvement of the Swat River in Pakistan. First, a four-point Likert scale was used to rank preferences for water quality benefits without using any financial metric. Results show that households have comparatively strong preferences for non-use benefits. Second, a contingent valuation question was designed to determine WTP for adopting a management plan developed exclusively for water quality improvement in the Swat River. The estimated annual mean WTP per household for water quality improvement is $2.40 when donating to an NGO. Generalizing this value to households living in Swat Valley would generate up to $544,000 per year. The present value aggregate benefit for 15 years would be sufficient to cover the present value of aggregate costs to adopt the management plan. A mandatory program that would require paying for the management plan generates half the WTP compared to the voluntary plan, but is still sufficient to cover costs and may be more feasible than a voluntary program because payment is assured.