A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

Investigation of long-term river water quality variations using different urbanization indices and assessment of common scientific perspectives of urbanization on water quality

This study investigated the water quality variation spanning 30 years (1986–2017) in 16 catchments of Hong Kong against different urbanization indices, namely, built area fraction; population; and product of population and built area fraction. Pearson correlations of three different periods of time (1988–1990, 1998–2000, and 2015–2017) indicated that water quality trends were dependent on the urbanization index. Total solids, nitrite-nitrogen, total phosphorus, electrical conductivity, dissolved oxygen, and flow rate had significant deteriorative trends (Pearson r > 0.5 and p < 0.05) with population and product of built area and population. Results also interpreted that built area fraction and product of built area and population were the worst and best indices that represented urbanization and/or its impacts, respectively. Mann-Kendall test for the entire 30 year period showed that water quality had improved with time with respect to certain water quality parameters (e.g., dissolved oxygen, ammoniacal nitrogen and total suspended solids). The results portrayed that although the urbanization of catchments had increased with time, the river water quality with respect to many parameters showed signs of improvement and the legislative measures implemented seemed to be effective in controlling pollution.     

Environmental justice in Nigeria: A narration of residents’ experience in Ile-Ife

The sharing of environmental cost by residents in various residential areas in the developing world is perceived to be unfair. This study therefore assessed residents’ experiences of environmental justice in Ile-Ife, Nigeria. Three residential areas were identified in the study area and samples were selected using systematic sampling. Using availability and condition of urban infrastructure, severity of environmental problems and residents’ involvement in environmental issues, the study examined environmental justice in the study area. The study established a variation in environmental issues across identified residential areas. The severity of environmental problem measured through an index tagged Severity of Environmental Problem (SEPI) revealed that environmental problems was most severe in the core (SEPI = 4.00), followed by the peripheral area (SEPI = 3.71) and least in the transition area (SEPI = 3.56). On the condition of available environmental infrastructure, the study revealed that the conditions of infrastructure were most improved in the peripheral area (ICI = 3.07), followed by the core (ICI = 2.67) and the least in the transition area (ICI = 2.42). The study concluded that residents’ experiences of environmental justice differ significantly across the different residential zones as reflected by residents’ socio-economic characteristics. Furthermore, it established that age, gender, educational status, and number of years spent in the area can be used to explain the differences in residents’ experience of environmental justice in the study area. To enhance the liveability, the study recommends adequate provision of environmental amenities needed by each category of people in the city.     

Five-wheel framework for system-based monitoring of heavy metal pollution in rivers

Sectorial approach for monitoring heavy metal pollution in rivers has failed to report realistic pollution status and associated ecological and human health risks. The increasing spread of heavy metals from different sources and emerging risks to human and environmental health call for reexamining heavy metal pollution monitoring frameworks. Also, the sources, spread, and load of heavy metals in the environment have changed significantly over time, requiring consequent modification in the monitoring frameworks. Therefore, studies on heavy metal monitoring in rivers conducted in the last decade were evaluated for experimental designs, research frameworks, and data presentations. Most studies (∼99%) (i) lacked inclusiveness of all environmental compartments; (ii) focused on “one pollutant – one/two compartment” or sometimes “one pollutant – one compartment – one effect” approach; and (iii) remained “data-rich but information poor.” An ecological approach with integrative system thinking is proposed to develop a holistic approach for monitoring river pollution. It is visualized that heavy metal monitoring, risk analyses, and water management must incorporate tracking pollutants in different environmental compartments of a river (water, sediment, and floodplain/bank soil) and consider correlating it with riverbank land use. The systems-based pollution monitoring and assessment studies will reveal the critical factors that drive heavy metals pollutant movement in ecosystems and associated potential risks to the environment, wildlife, and humans. Also, water quality and pollution indexing tools would help better communicate complex pollution data and associated risks among all stakeholders. Therefore, integrating systems approaches in scientific- and policy-based tools would help sustainably manage the health of rivers, wildlife, and humans.     

Changes in electrical generator cooling systems: Are they cost-effective sources of water now and under climate change?

In the United States, thermal power plant electrical generators (EGs) are large water diverters and consumptive users who need water for cooling. Retrofitting existing cooling systems to dry cooling and building new facilities with dry cooling can save water and reduce EG's vulnerability to drought. However, this can be an expensive source of water. We estimate that the cost of water saved by retrofitting cooling in existing EGs ranges from $0.04/m³ to $18/m³ depending on facility characteristics. Also water savings from building new EGs with dry cooling ranges in cost per unit water from $1.29/m³ to $2.24/m³. We compare costs with that for water development projects identified in the Texas State Water Plan. We find the water cost from converting to dry cooling is lower than many of the water development possibilities. We then estimate the impact of climate change on the cost of water saved, finding climate change can increase EG water use by up to 9.3% and lower the costs of water saved. Generally, it appears that water planners might consider cooling alterations as a cost competitive water development alternative whose cost would be further decreased by climate change.     

Public perception of air pollution sources across Europe

Air pollution is one of the primary concerns of our society for its effect on human health and the environment. Among the policy measures that can be put in place to limit air pollutant emissions, end-of-pipe technologies and/or regulatory instruments may be implemented through legislative acts. Also, equally important are behavioural measures, requiring citizens’ active involvement. The success of any measure to limit pollutant emissions requires the acceptance by the citizens that, in turn, implies a correct perception of the main pollutant emission drivers. We present here the comparison between the public perception of air pollution sources and the real-world situation through a survey carried out in seven European countries and involving 16 101 respondents. Our study shows a dramatic underestimation of the contribution of the agri-food sector to air pollution. This result is common to all respondents in the seven countries examined and only to a small extent depends on gender, age and socio-economic status of the respondents.     

Co-development of an integrated assessment framework to evaluate the effectiveness and impact of selected nature-based water treatment technologies in Sri Lanka,The Philippines,and Vietnam

Water quality is a critical challenge in Asia in the context of growing industrialization, urbanization, and climate change. Nature-based solutions (NbS) could play an important role in reducing urban water pollution, while generating multiple co-benefits that could make cities more liveable and resilient. In this regard, a number of pilot and demonstration projects have been set up to explore their potential across cities in Asia. Their effectiveness and impacts, however, have not been adequately documented, thus how they can be sustained, replicated and up-scaled remain poorly understood. This study aims to contribute to addressing this challenge by co-developing an integrated assessment framework and employing it to understand how existing evaluations of NbS in the region can be improved. It focuses specifically on a set of nature-based solutions that have been employed for water treatment across six cities in Southeast Asia (two in each Sri Lanka, the Philippines, and Vietnam), namely, floating wetlands, constructed wetlands and maturation ponds. The study also suggests specific methodologies for capturing a set of core indicators considered relevant for assessing the effectiveness and capturing the multi-faceted impacts of the examined NbS.     

Dynamic Bayesian networks for reliability evaluation of subsea wellhead connector during service life based on Monte Carlo method

The subsea wellhead connector is a critical connection component between subsea Christmas tree and subsea wellhead for preventing the leakage of oil and gas in the subsea production system. Excited by cyclical loadings due to environmental forces and the other support forces, the subsea wellhead connector is prone to the failure, which could lead to the loss of subsea tree or wellhead integrity and even catastrophic accidents. With the Monte Carlo simulation method, this paper presents a reliability analysis approach based on dynamic Bayesian Networks, aiming to assess the failure probability of the subsea wellhead connector during service life. Take the driving ring component of the subsea wellhead connector as an example to demonstrate the reasonability of the proposed model. The generation data is processed by the transform between the numerical value and the state variable. Based on the stress-strength interference theory, the structure reliability of the driving ring with 96.26% is achieved by the proposed model with the consideration the aging of the material strength and the most influential factors are figured out. Meanwhile, the corresponding control measures are proposed effectively reduce the failure risk of the subsea wellhead connector during service life.     

Institutional quality,financial development and sustainable economic growth among lower income countries

This article postulates strong endogenous relationships in lower income countries between institutional quality, financial development and sustained economic growth. These associations were investigated using the vector-error correction model (VECM) and Granger causality method for a sample of 79 countries from 2005 to 2022. The findings show that (1) these variables reinforce each other in the short run. (2) In the long run, both institutional quality and financial development can fuel economic growth. (3) The positive effect of institutional quality on economic growth is greater than that of financial development. Policy implications of these findings are that careful attention should be paid to co-development policies to enhance the institutional quality and the financial system in these economies. Policies should also consider economic growth strategies to enable sustainable economic growth rates.