Pollutant Export Research Articles

Landscape fragmentation of built-up land significantly impact on water quality in the Yellow River Basin

Urbanization development often leads to significant changes in the extent in area and fragmentation of built-up land landscape pattern (BLLP) in river basins, which greatly impact the processes of rainfall runoff and pollutant migration. Understanding the spatial scale effects and driving mechanisms of BLLP changes on water quality in large river basins is a challenging research topic and an international frontier in the interdisciplinary fields of geography and environment. This study analyzes the spatial variations of BLLP and water quality throughout the Yellow River Basin (YRB) during the rainy seasons from 2019 to 2021 (4hours scale). Utilized the random forest model to quantitatively separates the contributions of rainfall processes to surface runoff and water pollution, revealing the scale effects and non-linear driving mechanisms of BLLP impacts on water environment changes. The results indicate that: 1) The YRB exhibits great spatial heterogeneity in terms of both BLLP and water quality, with places with lower water quality displaying bigger areas and higher degrees of BLLP fragmentation. 2) The patch density and built-up land area (PD.B and CA.B) have a major impact on changes in water quality in the YRB, with notable impacts noted in circular buffer zones with radii of 20 km and 5 km, respectively. 3) PD.B is sensitive to water quality in the YRB, explaining 39.1% to 49.5% of the variance under different rainfall conditions, and exhibits a significant non-linear relationship, with an impact threshold of 0.38 (n/100 ha). The study suggests that for large-scale regions like the YRB, the degree of BLLP fragmentation is more likely to lead to degradation of water environmental quality compared to its area. BLLP fragmentation due to higher PD.B and CA.B disrupts the original ecosystem and hydrological connectivity, resulting in poorer retention and filtration of pollutants carried by rainfall runoff, while increasing the export of other pollutants. However, once urbanization surpasses a certain threshold, the BLLP fragmentation can enhance water quality by reducing the impermeable surface connectivity, as they are no longer impacted by expanding areas. To achieve ecologically sustainable development, it is necessary to apply rational landscape management and water resource management policies that consider the dual process of how BLLP fragmentation affects the water environment.

Air pollution and firms' export product quality: Evidence from China

AbstractThis study provides causal estimates of the effect of air pollution on firms' export product quality, based on China's experience. Using thermal inversions as an instrument, a 1% increase in PM2.5 is associated with a 0.25% decrease in export product quality. A series of tests indicates the robustness of our main result. Heterogeneity analysis reveals that the negative impact of air pollution on export product quality is only significant among regions with high levels of air pollution. In addition, we find that air pollution also reduces firms' export sales, share and probability. Our study provides original evidence for the relationship between air pollution and firms' export product quality, offering a unique perspective for countries to enhance export competitiveness.

Estimation of Pollution Export Coefficients of Tea Farms and Its Application in Watershed Management

Tea is an important economic crop worldwide, especially in Asian countries. However, tea cultivation requires substantial fertilizer use and may become a nutrient pollution source and affect water quality. This study presented two objectives: one was to estimate the pollution export coefficients of tea farms, and the other was to assess the performance of bioretention cells in terms of tea farm pollution control. This study employed a tea farm pollutant transport model (TPTM) and a watershed pollutant transport model (WPTM) to link watershed management goals and the tea farm control strategy. Field data collected for Jingualiao Creek in the Feitsui Reservoir watershed in Taipei, Taiwan, were analyzed. The resulting export coefficients for total phosphorus (TP), NH3-N, suspended solids (SS), and chemical oxygen demand (COD) were 2.55, 4.22, 768.39, and 145.71 kg/ha-y, respectively. Bioretention cells, which are low-impact development (LID) facilities and structural best management practices (BMPs), were installed and tested for their ability to reduce nonpoint source pollution. The field investigation and modeling results showed that 1 m2 of bioretention cells could reduce TP, NH3-N, SS, and COD by 18.6, 20.9, 5545.5, and 881.4 g/y, respectively. According to the WPTM results, 540 m2 of bioretention cells could achieve an 85% water quality attainment goal, and 715 m2 could reach 90% water quality attainment. Four tea farms covering 1.43 ha require 30.0 m2 of bioretention cells to achieve an 85% goal and 33.5 m2 to 90% goal. The export coefficients of tea nonpoint pollution sources presented in this study can serve as a valuable tool for estimating potential exported nutrients, and the field test results of bioretention cells are helpful information for policymakers in formulating effective watershed management measures.

Characterization and sources of water-soluble inorganic ions during sulfate-driven and nitrate-driven haze on the largest loess accumulation plateau

With the rapid reduction of anthropogenic SO2 emissions, the critical driver of haze in China has shifted from being dominated by sulfate to alternating sulfate and nitrate. Haze induced by different driver species may differ in the chemical forms of water-soluble inorganic ions (WSIIs). The unique topography and high-emission industrial agglomeration of the Loess Plateau determine its severe local PM2.5 pollution and influence global weather patterns through the outward export of pollutants. PM2.5 samples were conducted in Pingyao, on the eastern Loess Plateau of China, in autumn and winter. The average mass of PM2.5 was 88.82 ± 57.37 μg/m3; sulfate, nitrate, and ammonium were the dominant component. The chemical form of the ion was dominated by (NH4)2SO4, NH4NO3, NaNO3 and KNO3 during the nitrate-driven (ND) haze, while (NH4)2SO4, NH4HSO4, NH4NO3, NaNO3 and KNO3 were predominant species during the sulfate-driven (SD) haze. Heterogeneous oxidation reactions dominated the mechanism of sulfate formation. Primary sulfate emissions or other generation pathways contributed to sulfate formation during the SD haze. The gas-phase homogeneous reaction of NO2 and NH3 dominates the nitrate generation during the ND haze. The heterogeneous reactions also played an essential role during the SD haze. Nitrate aerosol (42.30%) and coal and biomass combustion (23.23%) were the dominant sources of WSIIs during the ND haze. In comparison, nitrate aerosol (31.80%) and sulfate aerosol (25.08%) were considered the primary control direction during the SD haze. The chemical characteristics and sources of aerosols under various types of haze differ significantly, and knowledge gained from this investigation provides insight into the causes of heavy haze.

Landscape pattern exhibits threshold-driven effect on nitrogen export of typical land use in subtropical hilly watershed under specific hydrological regimes

Landscape pattern can affect the export of non-point source nitrogen (N) in watersheds by regulating hydrological and biogeochemical processes. However, due to the inherent spatiotemporal variability of N exports under different land uses and hydrological regimes, it is essential to quantitatively evaluate the impact of landscape pattern on total N export coefficients (TNECs) and identify the threshold effect of TNECs between key landscape metrics. Based on river monitoring data for eight years in nine catchments of a typical agricultural watershed in the central subtropical region of China, we estimated the spatiotemporal variability and uncertainty of typical land-use TNECs (cropland, forest, and tea gardens) by combining an improved pollutant export coefficient model and Bayesian statistics. Subsequently, the contribution of landscape pattern to the variability in land use TNECs under different hydrological regimes was quantified, and the abrupt change points of TNECs along with the gradient of key landscape metrics were further determined. The results revealed that landscape pattern only had a significant effect on TNECs under medium-flow (representing discharge values within the 30–70th percentile range) and low-flow hydrological regimes (70–100th percentile range), explaining 48.1–54.7% and 55.2–69.3% of the variability, respectively. Threshold effects were observed between key landscape metrics representing different landscape categories (area edge, shape, and aggregation) and TNECs for each land use, and the threshold intervals corresponding to the TNEC abrupt change points were relatively consistent under medium- and low-flow regimes. These results serve as a critical reference for land-use planning and management to improve water quality, the approaches developed can be broadly extended to other regions with diverse land-use types and pollutant sources.

Green engineered mulch for phosphorus and metal removal from stormwater runoff in bioretention systems

Phosphorus and metals in stormwater runoff are major causes of water quality degradation. Bioretention systems are increasingly implemented to improve stormwater quality and to better manage stormwater quantity. Many studies have focused on modifying the composition of the soil bed to improve pollutant removal. However, the pollutant removal performance of bioretention systems can diminish over time, such as when clogging of the media occurs. Sediment accumulation on the soil surface may inhibit infiltration into the soil bed, thus limiting pollutant removal. Soil replacement may be eventually required as pollutants accumulate in the soil. In this study, a green retrofit material, called green engineered mulch (GEM), was generated by coating regular wood mulch with aluminum-based water treatment residuals (WTR) via a simple and low-energy process (patent pending). The GEM was developed to serve as a green retrofit for bioretention systems to enhance the removal of phosphorus and metals from stormwater runoff. The GEM was placed in a rain garden in Secaucus, NJ, USA for 15 months, during which 12 storm events (ranging from 6.0 mm to 89.6 mm) were monitored. Runoff and infiltrate samples were analyzed for dissolved and total concentrations of phosphorus and metals, along with other key water quality parameters. The GEM significantly reduced (p < 0.05) the total concentrations of phosphorus and metals in stormwater infiltrate compared to the inlet, unlike the regular mulch. Minimal or no contact with the GEM resulted in no significant pollutant removal from surface runoff. No significant pollutant export from the GEM was observed. The spent GEM can be disposed of as non-hazardous waste in municipal landfills. This study demonstrates that the GEM is a safe and effective retrofit. Moreover, the GEM is a simple and economical retrofit solution that can be used in place of regular mulch in bioretention systems.

Identification of pollutant delivery processes during different storm events and hydrological years in a semi-arid mountainous reservoir basin

A comprehensive understanding of pollutant delivery processes during storm events is essential for developing strategies to minimize adverse impacts on receiving water bodies. In this paper, hysteresis analysis and principal component analysis were coupled with identified nutrient dynamics to determine different pollutant export forms and transport pathways and analyze the impact of precipitation characteristics and hydrological conditions on pollutant transport processes through continuous sampling between different storm events (4 events) and hydrological years (2018-wet, 2019-dry) in a semi-arid mountainous reservoir watershed. Results showed pollutant dominant forms and primary transport pathways were inconsistent between different storm events and hydrological years. Nitrogen (N) was mainly exported in the form of nitrate-N(NO3-N). Particle phosphorous (PP) was the dominant P form in wet years, but total dissolved P (TDP) in dry year. Ammonia-N (NH4-N), total P (TP), total dissolved P(TDP) and PP had prominent flushing responses to storm events and were delivered mainly from overland sources by surface runoff; while the concentrations of total N(TN) and nitrate-N(NO3-N) were mainly diluted during storm events. Rainfall intensity and amount had significant control over P dynamics and extreme events played a key role in TP exports, accounting for >90 % of the total TP load exports. However, the cumulative rainfall and runoff regime during rainy season exerted significant control over N exports than individual rainfall features. In the dry year, NO3-N and TN were delivered primarily through soil water flow paths during storm events; nevertheless, wet year registered complex control on TN exports via soil water release, followed by surface runoff transport. Relative to dry year, wet year registered higher N concentration and more N load exports. These findings could provide scientific basis for determining effective pollution mitigation strategies in Miyun Reservoir basin and provide important references for other semi-arid mountain watersheds.

Hydro-chemical responses at different scales in a rural catchment, UK, and implications for managing the unintended consequences of agriculture

Diffuse pollutant transfers from agricultural land often constitute the bulk of annual loads in catchments and storm events dominate these fluxes. There remains a lack of understanding of how pollutants move through catchments at different scales. This is critical if the mismatch between the scales used to implement on-farm management strategies, compared to those used for assessment of environmental quality, is to be addressed. The aim of this study was to understand how the mechanisms of pollutant export may change when assessed at different scales and the corresponding implications for on-farm management strategies.A study was conducted within a 41 km2 catchment containing 3 nested sub-catchments, instrumented to monitor discharge and various water quality parameters. Storm data over a 24-month period were analysed and hysteresis (HI) and flushing (FI) indices calculated for two water quality variables that are typically of environmental significance; NO3–N and suspended sediment (SSC). For SSC, increasing spatial scale had little effect on the mechanistic interpretation of mobilisation and the associated on-farm management strategies. At the three smallest scales NO3–N was chemodynamic with the interpretation of dominant mechanisms changing seasonally. At these scales, the same on-farm management strategies would be recommended. However, at the largest scale, NO3–N appeared unaffected by season and chemostatic. This would lead to a potentially very different interpretation and subsequent on-farm measures.The results presented here underscore the benefits of nested monitoring for extracting mechanistic understanding of agricultural impacts on water quality. The application of HI and FI indicates that monitoring at smaller scales is crucial. At large scales, the complexity of the catchment hydrochemical response means that mechanisms become obscured. Smaller catchments more likely represent critical areas within larger catchments where mechanistic understanding can be extracted from water quality monitoring and used to underpin the selection of on-farm mitigation measures.

Effects of Livestock Exclusion on Pollutant Export From a North Carolina Beef Cow Pasture

Highlights Exclusion of beef cattle from two streams resulted in significant reductions in nitrogen, phosphorus, and sediment exports. Reductions in nutrient and sediment export improved following four or more years of exclusion. Nitrogen and phosphorus concentrations in storm samples decreased more than those in baseflow samples. Abstract. Fences were installed to exclude cattle from two adjacent small streams on a beef and swine farm located in central North Carolina. The two streams, referred to as UTA and North, originated in a pasture used for beef cow production and the application of swine waste. Rainfall and discharge were continuously monitored for 1.34 years prior to and 1.8 years after the fencing was installed in order to quantify the effect of the livestock exclusion on pollutant export/loads in the two streams originating in the pasture. Monitoring results documented reductions in total nitrogen (TN), phosphorus (TP), and total suspended solids (TSS) exports via the North stream of 15%, 54%, and 67%, respectively. Monitoring on the UTA stream was restarted 3.7 years after the initial 1.8 years and continued for about 1 year to assess the effect of natural vegetation growth and stream channel soil recovery. The combined reductions for the two periods were 39%, 64%, and 74% for TN, TP, and TSS, respectively. Exports of TN, TP, and TSS during the later monitoring period decreased by 13%, 60%, and 22%, respectively, compared to the initial 1.8-year monitoring period. These results indicated that exclusion fencing was effective at reducing pollutant exports during the first 1.8 years and that its effectiveness increased after about four years. Consequently, studies that report effectiveness during the first 2 to 4 years after exclusion likely underestimate the long-term effectiveness of the exclusion fencing. Keywords: Best management practices, Discharge monitoring, Livestock exclusion.

Influence of sampling frequency and estimation method on phosphorus load uncertainty in the Western Lake Erie Basin, Ohio, USA

Accurate estimates of nutrient loads are necessary to identify critical source areas and quantify the impact of management practices on pollutant export. Previous studies have investigated nutrient load estimate uncertainty, but they often focus on nutrient loads estimated using an interpolation method for large-scale watersheds with short-term datasets. The study objective was to quantify uncertainty in soluble reactive phosphorus (SRP), total phosphorus (TP), and suspended solids (SS) load estimates from two small (<103 km2) agricultural watersheds in the western Lake Erie Basin resulting from different sampling frequencies. Each watershed had high temporal resolution datasets of discharge (15 min) and nutrient concentration (1 to 3 samples per day) collected over a 30-year period (1990–2020). Firstly, SRP, TP, and SS loads were calculated using the high temporal resolution datasets, which was assumed as “true loads”. Secondly, the high temporal concentration data were decomposed to semiweekly, weekly, biweekly, and monthly sampling and annual loads were estimated using four common load estimation methods to assess the effect of sampling frequency and load estimation method on load estimate error. Across the four different methods, the composite method had the lowest relative root mean square and absolute bias, but the rectangular interpolation method was the most precise. However, even with semiweekly sampling, the composite method resulted in an unacceptable level of precision (average imprecision = 39 %), while the interpolation method resulted in an unacceptable bias (average absolute bias = 16 %). Because neither method could provide acceptable accuracy and precision at the lowest decrease in sampling (e.t. semiweekly sampling), continued daily sampling is recommended in these watersheds.

Calculation of seasonal agricultural grey water footprint in monsoon region based on river reference conditions

Grey water footprint accounting is of great significance to water resources management. The two important parameters of grey water footprint accounting, the natural background concentration of pollutants and the pollutant export coefficient, have obvious seasonal differences in the monsoon region, while the possible seasonal differences of grey water footprint in the monsoon region had been less considered in the previous research of grey water footprint accounting. This paper calculated the seasonal agricultural grey water footprint of Zhangjiakou City in North China by taking the river reference condition of total phosphorus as its natural background concentration and considering the seasonal difference of river reference condition of total phosphorus and the pollutant export coefficient. The results showed that the agricultural grey water footprint calculated with the reference condition of total phosphorus as the natural background concentration were 1.60 and 1.38 times of that calculated with zero as the natural background concentration in the rainy season and dry season, respectively. Due to the seasonal difference in the proportion of pollutants entering the river and the reference condition of total phosphorus, the agricultural grey water footprint showed obvious seasonal differences. The agricultural grey water footprint in rainy season was 11.73 times higher than that in dry season. In the composition of agricultural grey water footprint in Zhangjiakou from 2003 to 2018, the grey water footprint of livestock and poultry accounted for a large proportion. Districts and counties with relatively large agricultural grey water footprint in Zhangjiakou were concentrated in the south and north of Zhangjiakou, mainly including Zhuolu, Huailai, Yuxian, Xuanhua and Zhangbei; The districts and counties with relatively small agricultural grey water footprint were mainly located in the urban area of Zhangjiakou, including Qiaodong District, Qiaoxi District and Xiahuayuan District. This paper could clarify the seasonal difference of agricultural grey water footprint accounting in monsoon region and promote the development of grey water footprint accounting methods.

Optimal configuration of low impact development practices for the management of urban runoff pollution under uncertainty

The urbanization process has seen an accelerated increase in recent decades, leading to urban runoff pollution becoming more prominent. However, uncertainty of the pollution output and complexity of management systems have made controlling urban runoff pollution challenging. Therefore, it is necessary to propose advanced modeling methods for these challenges. This research presents an integrated urban runoff pollution management (IURPM) model for optimal configuration of low impact development (LID) practices under multiple uncertainties. The IURPM model combines the hybrid land-use prediction and improved pollution estimation models with interval parameter, stochastic parameter, and multi-objective programming. The proposed IURPM model can not only predict the output characteristics, but also provide optimal configuration schemes for the LID practices in the management of urban runoff pollution under multiple scenarios. In addition, uncertainties expressed as discrete intervals and probability density function in the management systems can be effectively addressed. A case study of the IURPM model was conducted in Dongguan City, South China. Results show that considerable amounts of urban runoff pollutants would export from Dongguan City by 2025. The export loads and pollution output flux per unit area would have significant spatial heterogeneity. The results further indicate that population size, gross domestic product, and regional area size are expected to play important roles in the pollution export, while impervious surface coverage and population density would likely have great influences on the output flux of urban runoff pollution. Based on the model findings, multiple LID practices should be adopted in Dongguan City to reduce the urban runoff pollution loads. Using the IURPM model, multiple LID implementation schemes can be obtained under different pollution reduction scenarios and significance levels, that can provide decision-making support for urban water environmental management, considering variations in the policymaker's decision-making preferences. This study demonstrates that the IURPM model can be applied to the optimal configuration of LID practices for the management of urban runoff pollution under uncertainty.

Green roof as an effective tool for sustainable urban development: An Australian perspective in relation to stormwater and building energy management

Green infrastructure could provide a suite of benefits, including stormwater management and climate change impact mitigation. While European countries, the USA and Canada are increasingly adopting green roofs, Australia is lagging behind. This study specifically reviews the performance of green roofs in terms of stormwater retention, runoff quality, building energy consumption and life cycle cost analysis, as well as policy development in the Australian context. Research studies on these topics within Australia are identified, collated and analysed with respect to other studies reported by reputable research groups in other countries, where the green roof system has already matured. It should be mentioned that the results related to energy consumption were from simulation studies and empirical evidence derived from limited case studies, as reported in the literature. This study found that the average water retention capacity (worldwide) of a green roof is around 66.2%, which is within to the values (60–70%) reported in Australian studies. Because of the high water retention capacity, green roofs limit the export of pollution for most storm events. But when green roofs are saturated, they may be a source of pollution. However, the concentration of the pollutant decreases significantly over time. The temperature reduction by green roofs in buildings ranges between 4 and 6 °C. There is a potential for energy savings in building heating and cooling, but the findings from the literature are highly variable (ranges between 9 and 50%). The average payback period reported for a green roof is about 16 years. However, this depends on the initial cost, maintenance and assumed discount rate in the study. It has been shown that government policies and public awareness are important to increase the green roof adoption rate. Finally, current challenges in adopting this technology and future research directions are summarised.

Optimization schemes for the spatially explicit management of small watersheds based on ecosystem disservices

Reasonable planning of spatially explicit management measures is key to effectively achieving management goals. In this study, we adopted a spatial conservation prioritization method, which combines functional zoning, ecosystem disservice bundles, and existing management measures, with the aim of developing optimal deployment plans in six small watersheds in northwestern Beijing. First, we investigated the existing management measures in the study areas and recorded their sizes, scopes, and effectiveness. Second, according to the management priority, we ranked pixels representing the study area with the Zonation 4.0 platform. The process is based on the ideas of both spatial conservation prioritization and how the seven ecosystem disservices (sediment export, nitrogen and phosphorus pollution export, surface runoff, quick flow, and risks of collapse and debris flow) distribute spatially. Finally, we moved the existing management measures to suitable higher priority locations by matching the management priority rank indicated by the pixels, the functional zoning, which represents the main environmental problems, and the land use/cover types. Additionally, the changes in the ecosystem disservices were evaluated before and after the optimization operation. The results showed that the pixels with a higher management priority were located mainly in the plain areas and the junctions of the mountains and the plains, where the main environmental problems were water pollution and quick flow. Most of the management measures, such as percolation drainage ditches and greening, were moved to the plains in the optimization scheme. The extents of the decreases in five ecosystem disservices (sediment export, nitrogen and phosphorus pollution export, surface runoff, and quick flow) after optimization exceeded 90% in the study areas. This study provided a method to develop the plans of spatially explicit management measures for watersheds, the application of which ensures a scientific basis for management planning. Widely applying this method would improve the effectiveness of spatial management measures.

Watershed health assessment using the coupled integrated multistatistic analyses and PSIR framework

Quantitatively assessing watershed health under anthropogenic activities and management responses is important for the scientific planning and management of watersheds. The current research on watershed health assessments insufficiently reflects watershed scale information from different dimensions, which leads to the incomplete understanding of watersheds and thus the lack of systematic management. This study investigated the health status in the Chaohu Lake watershed (CLW) based on monthly sampling data at 46 river sites in 2018. Watershed health assessment comprehensively considered four dimensions including socioeconomic and natural pressures, nonpoint pollution export, river water quality and management responses with the pressure-state-impact-response (PSIR) framework. Canonical correlation analysis (CCA) and variance partitioning analysis (VPA) were integrated to further quantify the inter-relationships among the variables of each PSIR index. An obstacle degree model was applied to examine the factors of mainly affecting the status of watershed health. The results showed that phosphorus, nitrogen and sediment exports of CLW increased more and river water quality in CLW worsened due to socioeconomic and natural pressures. Water quality improvement effectively responds to increasing woodland and grassland. Compared with natural factors, phosphorus, nitrogen and sediment exports had closer relationships with the pressures from socioeconomic activities. Moreover, socioeconomic pressures explained more changes in phosphorus and nitrogen exports, while natural factors explained relatively more changes in sediment exports. Phosphorus, nitrogen and sediment exports and woodland and grassland coverage explained <35 % of the variation in river water quality. Additionally, the obstacle degrees of pressures and phosphorus, nitrogen and sediment exports were lower, and the obstacle degrees of river water quality and woodland and grassland coverage were higher in urban sub-watersheds, which was the opposite in agricultural sub-watersheds. This research provides a new evaluation framework of watershed health and its obstacle factors, which is crucial to improve watershed health.

Coupling Two-Stage Stochastic Robust Programming with Improved Export Coefficient for Water Allocation among Industrial Sectors

Water scarcity and water pollution are essential factors limiting coordinated regional development, especially in water-deprived regions. Industrial restructuring is an effective water management solution to alleviate water scarcity and mitigate water pollution. However, due to widely existing inexact parameter information in the water resource management system, it is challenging to allocate water resources among industrial sectors. To address these problems, an export coefficient coupled with a two-stage stochastic robust programming method (EC-TSRP) was developed through integrating an export coefficient model (ECM), two-stage stochastic programming (TSP) and robust optimization. The proposed EC-TSRP model could effectively deal with the multiple uncertainties expressed as stochastic and the intervals with fluctuation ranges, and enhance the robustness of optimal plans for supporting water resource allocation among industrial sectors under complex uncertainties. It was then applied to Bayan Nur City, in arid north-west China. The optimization alternatives indicate that wheat, sheep and services would be the most sensitive sectors among all industrial sectors, when non-point source (NPS) pollution exports are restricted. In addition, comparing the EC-TSRP results with the deterministic model, the reliability of the system could be improved significantly, while the value of the objective function would be decreased slightly. The simulation results were also compared with the historical data from 2012 to 2016. Although the total revenue of Bayan Nur City would decrease by 1.52%, the pollutant loads of total nitrogen, total phosphorus and chemical oxygen demand (TN, TP and COD) would decrease by 14.5%, 7.75% and 2.07%, respectively, and total water allocation also would decrease from 4.6 billion m3 to 4.23 billion m3.

A Bayesian modeling framework to predict stormwater pollutant reduction in bioretention media

Bioretention is a green stormwater infrastructure practice that has been shown to reduce some of the harmful effects of urban stormwater on downstream receiving waters. Typically, media used for bioretention consist of high percentages of sand to realize high hydraulic conductivities and smaller percentages of soil or organic materials to improve the retention of stormwater pollutants. The objectives of this study were to evaluate four bioretention media mixes that differed in sand, compost, and water treatment residuals content and to predict pollutant removal based on realistic stormwater concentrations using Bayesian statistics. Pollutants of interest were chemical oxygen demand, ammonia, nitrite, nitrate, total Kjeldahl nitrogen, as well as total and dissolved forms of phosphorus, copper, lead, and zinc. Water quality data were collected for eleven storms, and cumulative rainfall after construction was used as a measure for the media age. The data were evaluated for the probability to observe pollutant reduction and for the probability to observe high-performance reduction (HPR) with a minimum pollutant reduction of 60%. The chemical oxygen demand had a probability for reduction of P = 0.09 and HPR of P = 0.00, resulting in pollutant export in the majority of storms. HPR reduction goals were met for total lead, zinc, and copper, and reduction probabilities were generally P > 0.5 for all total and dissolved metals. Age and media composition affected phosphorus and nitrogen removal, with increased pollutant retention observed as the media aged. Lower compost percentages resulted in less nutrient export. This probabilistic model of realistic stormwater concentrations in combination with bioretention pollutant removal experiments results in a holistic view of credible pollutant outflow concentrations that can be used by stormwater managers to alleviate the effects of stormwater on surface water quality.

Resource recovery and freshwater ecosystem restoration — Prospecting for phytoremediation potential in wild macrophyte stands

The primary aim of this study was to understand the factors, e.g., harvest frequency and plant community type, that can facilitate optimising phytoextraction in wild macrophyte communities as part of a strategy for water-quality improvement and resource recovery. This was achieved by surveying wild macrophyte communities and quantifying standing stocks of key nutrient pollutants such as N and P, and a range of other recoverable macro and micro-nutrients (Ca, K, Mg, Cu, Fe, Mn, Mo, Zn, Na and Cr). By scaling-up the pollutant export potential over a decade, it was determined which harvest strategy and plant community types provide the greatest levels of nutrient export. Grime’s CSR plant strategy framework was used to categorise each surveyed community, where large-statured, higher biomass producing competitor and stress tolerator-type communities were compared with ruderal-type communities that have rapid growth and high nutrient acquisition but smaller standing biomass and statures. High biomass plant communities containing competitor or stress tolerator species, produce greater standing stocks of macronutrients (such as N and P) for harvesting, while yields of micronutrient-type pollutants are more likely to be influenced by specific physiological traits that determine leaf tissue concentration. Utilising a high frequency harvest regime over a multi-year time scale suggested that small fast-growing ruderals could yield 4–6 times the concentration of macronutrients and micronutrients for export compared to competitor or stress tolerator-dominated communities e.g., P yields from ruderals were 25 g/m2 versus 5 g/m2 from competitor/stress tolerator-dominated communities. These results emphasise the need to consider both the plant community and the harvesting regime when using phytoextraction as a management tool. We anticipate that these results will help guide environmental managers in their approach in developing circular economy schemes that improve water quality through nutrient export.

Research on the Non-Point Source Pollution Characteristics of Important Drinking Water Sources

In recent years, freshwater resource contamination by non-point source pollution has become particularly prominent in China. To control non-point source (NPS) pollution, it is important to estimate NPS pollution exports, identify sources of pollution, and analyze the pollution characteristics. As such, in this study, we established the modified export coefficient model based on rainfall and terrain to investigate the pollution sources and characteristics of non-point source total nitrogen (TN) and total phosphorus (TP) throughout the Huangqian Reservoir watershed—which serves as an important potable water source for the main tributary of the lower Yellow River. The results showed that: (1) In 2018, the non-point source total nitrogen (TN) and total phosphorus (TP) loads in the Huangqian Reservoir basin were 707.09 t and 114.42 t, respectively. The contribution ratios to TN export were, from high to low, rural life (33.58%), farmland (32.68%), other land use types (20.08%), and livestock and poultry breeding (13.67%). The contribution ratios to TP export were, from high to low, rural life (61.19%), livestock and poultry breeding (21.65%), farmland (12.79%), and other land use types (4.38%). The non-point source pollution primarily originated from the rural life of the water source protection zone. (2) Non-point source TN and TP pollution loads and load intensities showed significantly different spatial distribution patterns throughout the water source protection area. Specifically, their load intensities and loads were the largest in the second-class protected zone, which is the key source area of non-point source pollution. (3) When considering whether to invest in agricultural land fertilizer control or rural domestic sewage, waste, and livestock manure pollution control, the latter is demonstrably more effective. Thus, in addition to putting low-grade control on agricultural fertilizer loss, to rapidly and effectively improve potable water quality, non-point source pollution should, to a larger extent, also be controlled through measures such as establishing household biogas digesters, introducing village sewage treatment plants, and improving the recovery rate of rural domestic garbage. The research results discussed herein provide a theoretical basis for formulating a reasonable and effective protection plan for the Huangqian Reservoir water source and can potentially be used to do the same for other similar freshwater resources.

Prediction and optimization of regional land-use patterns considering nonpoint-source pollution control under conditions of uncertainty

Socioeconomic development, leading to significant changes in land-use patterns, has further influenced the output of regional nonpoint-source (NPS) pollution. Multiple uncertainties exist in the processes of land-use changes and NPS pollution export. These uncertainties can deeply affect the management of regional land-use patterns and control of NPS pollution. In this research, an integrated land-use prediction and optimization (ILUPO) model based on system dynamics, export coefficient, interval linear programming, and fuzzy parameter programming models was proposed. The ILUPO model can provide future land-use patterns and NPS pollution loads, and also help optimize the patterns under multiple pollution reduction scenarios. Interval and fuzzy uncertainties in the processes of land-use changes and NPS pollution output can be effectively addressed. The developed model was applied to a water source area in the central part of northern Guangdong Province in South China. For the prediction period 2020–2030 under the high-speed development scenario, results show that cropland area would decrease, while grassland and waterbody areas would increase. In contrast, these three types of land-use would show opposite variation trends under the low-speed development scenario. Construction land area would decrease, while forestland area would increase under both the low-speed and high-speed development scenarios. Variation of the predicted land-use patterns would lead to an increase of total nitrogen loads under each of the scenario, while the total phosphorus loads would show relatively complex variation trends. Regional land-use patterns should be further optimized to mitigate NPS pollution. However, the pollution loads in the study area cannot be reduced by >5% through land-use adjustment. Because cropland would still be the critical source of NPS pollution after optimization, strictly controlling the areas of cropland would be important for the management of such pollution in the research area. In addition, certain areas of grassland and waterbody would need to be converted into cropland and construction land to balance the economic benefit of the system and NPS pollution control. Multiple results obtained from the model under different scenarios of pollution reduction targets and α-cut levels can provide decision-making supports for the local policy makers. The developed ILUPO model can yield insights useful for the planning and adjustment of regional land-use patterns while considering NPS pollution control under conditions of uncertainty.