Coupling with high-resolution remote sensing data to evaluate urban non-point source pollution in Tongzhou, China

Spatiotemporal drivers of urban water pollution: Assessment of 102 cities across the Yangtze River Basin

Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors, offering crucial insights for basin administrators. Yet, comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce. Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin, analyzing water quality data from 102 cities during 2018-2019. We assessed the exceedance rates for six pivotal indicators: dissolved oxygen (DO), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total phosphorus (TP), and the permanganate index (CODMn) for each city. Employing random forest regression and SHapley Additive exPlanations (SHAP) analyses, we identified the spatiotemporal factors influencing these key indicators. Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators, thus pinpointing them as the leading pollution source in the basin. Additionally, forest coverage, livestock farming, chemical and pharmaceutical sectors, along with meteorological elements like precipitation and temperature, significantly impacted various indicators' exceedances. Furthermore, we delineate five core urban risk components through principal component analysis, which are (1) anthropogenic and industrial activities, (2) agricultural practices and forest extent, (3) climatic variables, (4) livestock rearing, and (5) principal polluting sectors. The cities were subsequently evaluated and categorized based on these risk components, incorporating policy interventions and administrative performance within each region. The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors, especially for cities presenting elevated risk levels.

Understanding phosphorus fractions and influential factors on urban road deposited sediments

Phosphorus (P) is a primary pollutant that builds-up on urban road surfaces. Understanding the fraction and load characteristics of P, as well as their relationship with urban factors, is helpful for assessing the ecological risk of urban receiving water bodies. This study presents the characteristics of build-up loads of P fractions in road-deposited sediments (RDS) in Guangzhou, China, analyzes their correlation with three urban factors (road, traffic, and land-use area), and then estimates the exceedance probability of P in stormwater runoff over the past 10 years. The results showed that detrital apatite phosphorus (De-P) performed the highest build-up load on urban road surfaces, followed by apatite phosphorus (Ca-P), iron-bound phosphorus (Fe-P), exchangeable phosphorus (Ex-P), aluminum-bound phosphorus (Al-P), organophosphorus (POP), dissolved inorganic phosphorus (DIP), occluded phosphorus (Oc-P), and dissolved organic phosphorus (DOP). Depression depth, road materials, and land-use fractions affected the P fractions. The P in the RDS may have originated from three distinct sources: road background, domestic waste, and untreated wastewater discharge. In the most recent 10 years, the event mean concentrations of total P in the RDS have had a 30 % probability of exceeding 0.4 mg L-1, which indicates a serious threat of P to receiving water bodies. The outcomes of this study are expected to provide valuable guidance for elucidating the principal categories of urban non-point source P pollution and enhancing the ecological health of urban water environments.

Enhancing phosphorus source apportionment in watersheds through species-specific analysis

Phosphorus (P) is a pivotal element responsible for triggering watershed eutrophication, and accurate source apportionment is a prerequisite for achieving the targeted prevention and control of P pollution. Current research predominantly emphasizes the allocation of total phosphorus (TP) loads from watershed pollution sources, with limited integration of source apportionment considering P species and their specific implications for eutrophication. This article conducts a retrospective analysis of the current state of research on watershed P source apportionment models, providing a comprehensive evaluation of three source apportionment methods, inventory analysis, diffusion models, and receptor models. Furthermore, a quantitative analysis of the impact of P species on watersheds is carried out, followed by the relationship between P species and the P source apportionment being critically clarified within watersheds. The study reveals that the impact of P on watershed eutrophication is highly dependent on P species, rather than absolute concentration of TP. Current research overlooking P species composition of pollution sources may render the acquired results of source apportionment incapable of assessing the impact of P sources on eutrophication accurately. In order to enhance the accuracy of watershed P pollution source apportionment, the following prospectives are recommended: (1) quantifying the P species composition of typical pollution sources; (2) revealing the mechanisms governing the migration and transformation of P species in watersheds; (3) expanding the application of traditional models and introducing novel methods to achieve quantitative source apportionment specifically for P species. Conducting source apportionment of specific species within a watershed contributes to a deeper understanding of P migration and transformation, enhancing the precise of management of P pollution sources and facilitating the targeted recovery of P resources.

Fluorescence fingerprint as an indicator to identify urban non-point sources in urban river during rainfall period

Nowadays, the urban non-point source (NPS) pollution gradually evolved as the main contributor to urban water contamination since the point source pollution was effectively controlled. It was imperative to perform urban NPS identification in urban river to meet the requirements of precise source governance. In this study, the real-time detection about water quality parameters and fluorescence fingerprints (FFs) was performed for BX River and its outlets during rainfall period. EEM-PARAFAC and component similarity analyses discovered that the pollution encountered by BX River mainly came from road runoff and untreated municipal wastewater (UMWW) overflow. The C1 (tryptophan-like) and C3 (terrestrial humic-like) components located at Ex/Em = ∼230(280)/340 and ∼275/430 nm were both detected in these two kinds of urban NPS. The C2 components of road runoff and UMWW overflow displayed remarkable differences, which located at Ex/Em = 250/385 and 245/365 nm, respectively, thus could be served as indicators for distinguishing them. During rainfall period, the outflow from rainwater outlets (RWOs) constantly showed similar FF features to road runoff, while the FFs of outflow from combined sewer outlets (CSOs) alternated between those of road runoff and UMWW overflow. The FF features of sections in BX River changed in response to the dynamic variations in FFs of the outlets, which revealed real-time pollution causes of BX River. This work not only realized the identification and differentiation of urban NPS, but also elucidated the dynamic variations of pollution characteristics throughout the entire process of "urban NPS-outlets-urban river", and demonstrated the feasibility of FF technique in quickly diagnosing the pollution causes of urban river during rainfall period, which provided important guidance for urban NPS governance.

Transport dynamics of watershed discharged diffuse phosphorus pollution load to the lake in middle of Yangtze River Basin

Diffuse pollution, including that in the lower and middle reaches of the Yangtze River, is the primary source of pollution in several agricultural watersheds globally. As the largest river basin in China, the Yangtze River Basin has suffered from total phosphorus (TP) pollution in the past decade owing to diffuse pollution and aquatic ecology destruction, especially in the midstream tributaries and mid-lower reaches of the lakes. However, the transport dynamics of diffuse pollutants, such as phosphorus (P) from land to water bodies have not been well evaluated, which is of great significance for quantifying nutrient loss and its impact on water bodies. In this study, diffuse pollution estimation with remote sensing (DPeRS) model coupled with Soil and Water Assessment Tools (SWAT) was utilized to simulate the transport dynamics of P, investigate the spatial heterogeneity and P sources in the Poyang Lake Basin. Additionally, the P transport mechanism from land to water and the migration process in water bodies were considered to investigate the impact of each loss unit on the water body and evaluate the load generated by diverse pollution types. The estimated diffuse TP loss was 6016 t P·yr-1, and the load to inflow rivers and to Poyang Lake were 11,619 and 9812 t P·yr-1, respectively. Gan River Basin (51.09%) contributed most TP to Poyang Lake among five inflow rivers, while waterfront area demonstrated the highest TP load per unit area with 0.057 t km-2·yr-1. Our study also identified P sources in the sub-basins and emphasized agricultural diffuse sources, especially planting, as the most significant factor contributing to TP pollution. Additionally, to improve the aquatic environment and water ecological conditions, further nutrient management should be applied using a comprehensive approach that encompasses the entire process, from source transportation to the water body.

Water quality improvement project for initial rainwater pollution and its performance evaluation

Efficiently addressing initial rainwater pollution is crucial for mitigating urban water pollution. However, the performance evaluation of initial rainwater pollution control project is rarely introduced. In this study, the architecture of effective comprehensive engineering measures for improving the water quality of initial rainwater in Anhui Province, China, was described. Three water quality indicators, ammonia nitrogen (NH3-N), chemical oxygen demand (COD), and total phosphorus (TP), were selected to explore the severity of urban pollution caused by initial rainwater under various rainfall scenarios. A single-factor evaluation method was used to contrast and assess the benefits of the initial rainfall interception project in terms of water quality enhancement. Results showed that initial rainfall pollution was gentler under light rainfall conditions but more prominent under moderate and heavy conditions. The percentages of NH3-N, COD, and TP in Lotus Pond that met the tertiary drinking water standard were 100%, 74.91%, and 100% with great improvement, and the average concentrations of NH3-N, COD, and TP in Fushan Road Drainage have decreased by 91.43%, 10.49%, and 57.33% respectively, after the construction of the interception project. These indicated that the nitrogen and phosphorus pollution were successfully controlled by the control techniques in both locations, but COD concentration has to be addressed with more specialized strategies. Overall, the water quality improvement project for initial rainwater pollution plays a great role in effectively governing initial rainwater pollution and improving river water quality, and provides an effective technical reference for urban water ecological environment management.

The spatial distribution of microplastics in topsoils of an urban environment - Coimbra city case-study

Due to their seemingly ubiquitous nature and links to environmental and human health problems, microplastics are quickly becoming a major concern worldwide. Artificial environments, such as those found in urban environments, represent some of the main sources of microplastic. However, very few studies have focused on the occurrence of microplastics in urban soils. The aim of the current research was to evaluate the microplastic contamination in urban soils from artificial and natural land uses throughout Coimbra city, Portugal. Sixty-seven spaces and ten land use areas were evaluated. The artificial land use areas were dumps, landfills, parking lots, industries and construction areas, and the natural land use areas were forests, urban parks, moors (wetlands), pastures and urban agricultural areas. Microplastic extraction was done by density separation. Quantification and size measurements of microplastics was carried out using a microscope. Polymer types were identified by μ-FTIR for 25% of the samples. The microplastic content ranged from 5 × 10³ to 571 × 10³ particles·kg^-1, with a mean of 106 × 10³ particle·kg^-1. The green park was the land use with the highest concentration of microplastics (158 × 10³ particle·kg^-1) and the forest was the one with the lowest concentration (55 × 10³ particle·kg^-1). The landfill (150 × 10³ particle·kg^-1), industry (127 × 10³ particle·kg^-1) and dump (126 × 10³ particle·kg^-1) were the artificial spaces with the highest levels of microplastics. The main polymers detected were polypropylene and polyethylene, followed by polyvinyl chloride and rubber, and the main sizes measured between 50 and 250 μm. Our results indicate that natural spaces can contain higher amounts of microplastics as compared to artificial spaces in the urban environment. This suggests that microplastics are easily transported through the urban landscape and that urban green spaces can retain microplastics in their soils. Land use planning may present an opportunity to better control the levels of microplastics in urban environments.

Monitoring of urban ecological environment including air quality using satellite imagery

Rapid urbanisation has highlighted problems in the urban ecological environment and stimulated research on the evaluation of urban environments. In previous studies, key factors such as greenness, wetness, and temperature were extracted from satellite images to assess the urban ecological environment. Although air pollution has become increasingly serious as urbanisation proceeds, information on air pollution is not included in existing models. The Sentinel-5P satellite launched by the European Space Agency in 2017 is a reliable data source for monitoring air quality. By making full use of images from Landsat 8, Sentinel-2A, and Sentinel-5P, this work attempts to construct a new remote sensing monitoring index for urban ecology by adding air quality information to the existing remote sensing ecological index. The proposed index was tested in the Beijing metropolitan area using satellite data from 2020. The results obtained using the proposed index differ greatly in the central urban region and near large bodies of water from those obtained using the existing remote sensing monitoring model, indicating that air quality plays a significant role in evaluating the urban ecological environment. Because the model constructed in this study integrates information on vegetation, soil, humidity, heat, and air quality, it can comprehensively and objectively reflect the quality of the urban ecological environment. Consequently, the proposed remote sensing index provides a new approach to effectively monitoring the urban ecological environment.

Response Model for Urban Area Source Pollution and Water Environmental Quality in a River Network Region

With the development of cities, urban area source pollution has become more severe and a significant source of water pollution. To study the relationship between urban area source pollution and water environmental quality in a river network, this study uses a city in the Yangtze River Delta, China, as an example. The Storm Water Management Model (SWMM) model and the MIKE11 model were combined into a unified modeling framework and used to simulate dynamic changes in the water quality of a river network under light rain, moderate rain, and heavy rain. In the study period, the annual urban area source input loads of potassium permanganate (COD_Mn), total phosphorus (TP), and ammonia nitrogen were 29.8, 0.9, and 4.8 t, respectively. The influence of light rain on the water quality of the river network was lagging and temporary, and rainfall area pollution was the primary contributor. Under the scenario of moderate rain, overflow from a pipeline network compounded rainfall runoff, resulting in a longer duration of impact on the water quality in the river. Additionally, the water quality in the river course was worse under moderate rain than under light or heavy rain. Under the scenario of heavy rain, rain mainly served a dilutive function. This research can provide support for urban area source pollution control and management.