Policy choice and riverine water quality in developing countries: An integrated hydro-economic modelling approach

Plants' emission behaviors under dual control of pollutant concentration and quantity

Quantity-based and concentration-based limits are two common environmental permitting approaches utilized by government worldwide in environmental management. While existing literature is still unambiguous about roles played by quantity-based versus concentration-based limits in environmental management, it becomes evident that relying exclusively on concentration-based or quantity-based limits to control plant emissions may not necessarily result in improved environmental quality. This paper leverages a unique opportunity arising from a recent reform in China's Pollutant Emission Permit System (PEPS) initiated in 2016 to analyze how the introduction of quantity-based limits in addition to concentration-based limits through the PEPS reform impact emissions at the plant level. Utilizing a unique plant-level continuous emission monitoring system data collected from Shaanxi Province (located in western China), the paper finds a significant reduction in air pollutant emissions as a result of the PEPS reform (nitrogen oxides (NOx) by 39%, sulfur dioxide (SO2) by 15% and particulate matter (PM) by 13%). The heterogeneity analyses show emission reductions in plants differ across those with varying quantity limits specified in their permits, distinct emission ratios and diverse ownership structures. Furthermore, plants that fall under the classified management system with more stringent regulations imposed, especially those operating in high-pollution sectors, situated within industrial parks, or classified as large-sized plants, attain higher pollutant quantity limits. Findings of the paper carry important implications for effective environmental management, particularly within developing countries, and shed some light on carbon emission reduction policies in China.

Assessing surface water pollution in Hanoi, Vietnam, using remote sensing and machine learning algorithms

Rapid urbanization led to significant land-use changes and posed threats to surface water bodies worldwide, especially in the Global South. Hanoi, the capital city of Vietnam, has been facing chronic surface water pollution for more than a decade. Developing a methodology to better track and analyze pollutants using available technologies to manage the problem has been imperative. Advancement of machine learning and earth observation systems offers opportunities for tracking water quality indicators, especially the increasing pollutants in the surface water bodies. This study introduces machine learning with the cubist model (ML-CB), which combines optical and RADAR data, and a machine learning algorithm to estimate surface water pollutants including total suspended sediments (TSS), chemical oxygen demand (COD), and biological oxygen demand (BOD). The model was trained using optical (Sentinel-2A and Sentinel-1A) and RADAR satellite images. Results were compared with field survey data using regression models. Results show that the predictive estimates of pollutants based on ML-CB provide significant results. The study offers an alternative water quality monitoring method for managers and urban planners, which could be instrumental in protecting and sustaining the use of surface water resources in Hanoi and other cities of the Global South.

Divisional water quality management-based pollution source control in China's watersheds: an analysis by introducing economic factors

Divisional water quality management (DWQM) is widely adopted in watershed pollution control. During 2011-2015, China zoned 708 priority controlled areas (PCAs) and 774 non-priority controlled areas (NPCAs) for key watersheds. DWQM at watershed level provides guidance on pollution source control (PSC) at local (provincial, city, and county) level. To identify the consistency between DWQM and PSC, a total of 29,688 enterprise-level data from China was analyzed with the difference-in-difference model. The economic factors that affect both are adopted to identify the causes of the disparities between them. The results show that PCAs were more effective than NPCAs and non-controlled areas (NCAs) in reducing COD emissions, thus better achieving divisional water quality goals. NPCAs were no more effective in reducing COD emissions than NCAs. Local government administration and potential subsidies are key to COD emission reductions, but they do not encourage technological progress. Lesser COD emission reductions were achieved in China's national key ecological function zones (NKEFZs) and upstream areas than in other areas. Current DWQM potentially aimed at relatively short-term economic benefits, which led to inconsistency with PSC particularly in NPCAs. To improve the coordination between them, ecological integrity should be the focus. Market-based watershed funding mechanism, especially watershed ecological compensation, transforms the short-term economic welfare from pollution control into long-term watershed ecological benefits.

Dynamic simulation of industrial synergy optimisation pathways in Beijing-Tianjin-Hebei region driven by water environment improvements

China is promoting the coordinated development of the Beijing-Tianjin-Hebei region as a national strategy project; however, water scarcity and water quality problems will become a bottleneck restricting high-quality development. This study aimed to explore a feasible industrial synergy optimisation pathway to realise the collaborative development of economic growth and water environment improvement, combined with incentives for environmental efficiency improvement and reclaimed water utilisation. Research methods integrate input-output modelling, system dynamics, and multi-objective programming to construct a complex multi-region model. A dynamic simulation measure was adopted to simulate the economic and environmental impacts of different approaches that mix from 2020 to 2030 under water resource environment constraints. According to the simulation results, the annual economic growth rate of the entire region can exceed 6.1%, and the emission intensities of water pollutants decrease by more than 60.0%. In addition, traditional manufacturing industries that achieve cross-regional synergy can still release location advantages without negative environmental impacts. Furthermore, regional collaborative development optimises the allocation of water resources and alleviates water stress. Moreover, the pollutant emission reduction effect of source control in Hebei was more effective than in other cities. Finally, reclaimed water, as the end treatment measure, has the largest marginal effect on improving the trade-off between economic and environmental improvement in the long run. This study provides a new approach for multi-regional industrial synergy development and optimal allocation of resources and contributes to the high-quality development of the watershed.

A multi-pronged approach to source attribution and apportionment of heavy metals in urban rivers

Heavy metal (HM) contamination of water bodies is caused by both first generation (industries) and second generation (distributed sources, domestic sewage, sediments) sources. We applied a multi-pronged approach to quantify the contribution of first and second generation sources to the HM load in a stream located in an industrialised catchment. We found that, despite strict regulation, first generation sources contributed significantly to the HM load (60%-80%), showing the ineffectiveness of current regulation. Domestic sewage contributed significantly to Cu, Ni, and Mn load (15%-20%). The contribution of distributed sources and sediments to HM load is insignificant. In a 24-hour cycle, HM concentrations frequently exceeded FAO's irrigation water quality standards, with the highest concentrations observed at night. Empirically, the study highlights the continued plight of urban streams in rapidly industrialising centers and the failure to regulate first-generation sources. Methodologically, it demonstrates the importance of temporally intensive measurement of contaminant concentration and load. Policy implications include the need for ambient water quality standards, inclusion of HMs in such standards, load-based regulation, and a problem-oriented monitoring and enforcement approach.

An interval two-stage fuzzy fractional programming model for planning water resources management in the coastal region - A case study of Shenzhen, China

In this study, an interval two-stage fuzzy fractional programming (TFFP) method is developed to facilitate collaborative governance of economy and water resources. Methods of interval programming, fuzzy programming, two-stage programming, and fractional programming are integrated within a general system optimization framework. The main contribution of TFFP is simultaneously addressing various uncertainties and tackling trade-offs between environmental and economic objectives in the optimized schemes for water resources allocation. A case study of a highly urbanized coastal city (i.e., Shenzhen) in China is provided as an example for demonstrating the proposed approach. According to the results, industrial sectors should receive 34.8% of total water supply, while agricultural sectors should receive 1.5%. For the spatial allocation of water resources, Bao An, Long Gang, and Fu Tian districts should be allocated 21.6%, 20.5%, and 14.8% water to promote the economic development. The discharge analysis indicates that chemical oxygen demand (COD_cr) and total phosphorus (TP) would be key pollutants. Moreover, the optimized seawater desalination volume would be negligibly influenced by price, while the upper bounds of desalination would be increased with the raising acceptable credibility levels in the period of 2031-2035. Analysis of desalination prices also reveals that the decision-makers should increase the scale of desalination in the period of 2021-2025. In addition, the effectiveness and applicability of TFFP would be evaluated under economic maximization scenarios. The result showed that the economic maximization scenario could obtain higher economic benefits, but it would be accompanied by a larger number of pollutant discharges. It is expected that this study will provide solid bases for planning water resources management systems in coastal regions.

An Overview of Ecosystem Service Studies in a Tropical Biodiversity Hotspot, Sri Lanka: Key Perspectives for Future Research

Tropical island countries are often highly populated and deliver immense ecosystem service benefits. As human wellbeing depends on these ecosystems, proper management is crucial in the resource-rich tropical lands where there is less related research. Though ecosystem service and biodiversity studies are a promising path to inform the ecosystem management for these mostly developing countries, published evidence of using ecosystem service studies in decision making is lacking. The purpose of this study is to provide an overview of ecosystem services and related research in Sri Lanka, examining trends and gaps in how these studies are conceptualized. Out of the considered 220 peer-reviewed articles, the majority of articles (48.2%) were terrestrial and forest related while coastal ecosystems were considered in 33.2% of studies. In most studies, the ecosystem service category studied was provisioning (31.5%) followed by regulatory service (28.7%). Studies investigating and quantifying ecosystem services, pressures on ecosystems, and their management were fewer compared to studies related to biodiversity or species introduction. Moreover, studies investigating the value of ecosystem services and biodiversity to the communities or involvement of stakeholders in the development of management actions regarding the ecosystem services were rare in Sri Lanka, and an intense focus from future studies in these aspects is timely and necessary.

Decision Support for the (Inter-)Basin Management of Water Resources Using Integrated Hydro-Economic Modeling

The development of adequate modeling at the basin level to establish public policies has an important role in managing water resources. Hydro-economic models can measure the economic effects of structural and non-structural measures, land and water management, ecosystem services and development needs. Motivated by the need of improving water allocation using economic criteria, in this study, a Spatial Decision Support System (SDSS) with a hydro-economic optimization model (HEAL system) was developed and used for the identification and analysis of an optimal economic allocation of water resources in a case study: the sub-middle basin of the São Francisco River in Brazil. The developed SDSS (HEAL system) made the economically optimum allocation available to analyze water allocation conflicts and trade-offs. With the aim of providing a tool for integrated economic-hydrological modeling, not only for researchers but also for decision-makers and stakeholders, the HEAL system can support decision-making on the design of regulatory and economic management instruments in practice. The case study results showed, for example, that the marginal benefit function obtained for inter-basin water transfer, can contribute for supporting the design of water pricing and water transfer decisions, during periods of water scarcity, for the well-being in both basins.