The changes in diatom assemblages along an urban-to-rural gradient were characterized to assess the ecological status of the Sai Gon River, Vietnam. Diatoms and physico-chemical variables were measured at 10 stations during dry and rainy season. One-way ANOVA showed that diatom metrics and physicochemical variables were significantly different (p < 0.05) between the upper course sites and both the middle- and the lower sites. However, no significant differences were observed between the middle course sites and the lower course sites. Achnanthidium minutissimum and A. exigua were potential indicators of low nutrient in the upper course sites; Melosira granulata and Navicula viridula were preferred moderately eutrophic water in the middle course sites; while Navicula cryptocephala and Nitzschia palea were tolerant to very heavy pollution and dominant in the lower course sites. Canonical correlation analysis (CCA) results showed that concentration of TSS, TN, TP, BOD5 and COD were the most important factors in structuring benthic diatom communities in the Sai Gon River. The results of this study indicated that diatom community was sensitive to changes in urban condition and could be used as an indicator of urbanization.

Eutrophication of the urban water bodies is one the biggest challenge causing severe ecological and economic loss. Urban ponds are more prone to eutrophication due to their small size and polluted catchment areas. Biomonitoring using phytoplankton provides cost-effective estimation of the level of eutrophication. Ten urban ponds in different areas of the Mumbai city were chosen to investigate the phytoplankton community structure, and level of eutrophication. We assessed the 3 algal indices viz. Shannon-Wiener indices, Palmer and Nygard's (Myxophycean and diatom) indices. Linear relationship of these indices was tested against Carlson trophic state indices in order to assess the effectiveness of these indices to measure the degree of eutrophication in urban lakes. All ten lakes were found to be eutrophic, of which two were very low eutrophic (TSI – 53.74-53.95), four were low-mid eutrophic (TSI – 55.18 – 57.5), and four lakes were mid eutrophic (TSI 61.4 – 62.2). Shannon-Wiener indices (r= -0.73) and Myxophycean indices (r= 0.77) showed strong correlation with TSI whereas Diatom indices (r= -0.12) and Palmer’s Algal Pollution Indices (r= - 0.47) showed weak correlation with TSI. Thus study found that Shannon-Wiener indices and Myxophycean indices are reliable and cost effective means to assess the eutrophication of urban ponds in Mumbai.

Fine particulate matter (PM2.5) have not only detrimental impacts on air quality but also acts as a source for a range of heavy metals that worsen the potential risks to public health. Notably, previous studies on PM2.5-bound heavy metals in Pakistan have primarily focused on individual cities. This study offers a comprehensive analysis of pollution characteristics related to PM2.5-bound heavy metals, including lead (Pb), cadmium (Cd), zinc (Zn), and nickel (Ni), in ten cities of Pakistan. Data was collected from a wide range of reliable sources spanning from 2013 to 2023. Additionally, the human health risk assessment methodology endorsed by the United States Environmental Protection Agency (US EPA) was employed to evaluate both carcinogenic and non-carcinogenic risks for adults (males and females) and children. Findings of the present study revealed that children faced a greater risk associated with PM2.5-bound heavy metals as compared to adults. Cadmium, zinc, and nickel were found as the top three contributors to the average non-carcinogenic risk, while lead, cadmium, and nickel showed the highest carcinogenic risks. Based on these findings, this study strongly recommend that the government should strengthen the management of industrial and vehicular emissions. Furthermore, there is an imperative need to establish a real-time monitoring system capable of tracking toxic heavy metal pollutants transported through the atmosphere. Additionally, policymakers should seriously contemplate regional collaborations with the goal of creating metropolitan initiatives for pollution control, thereby effectively addressing these paramount environmental and public health concerns.

The present study aims at investigating land use changes (as one of the effective human factors on water systems) as well as its relation with water quality at spatial scales of the entire basin, sub-basin and defined buffers (10 and 15 km) in Zayandeh-Rud Basin, Isfahan, Iran. By means of supervised classification method along with maximum likelihood algorithm, it classifies the land use map into five categories, including agriculture, bare lands, urban areas, vegetation, and water. The research collects data for 11 water quality parameters in seven sampling stations of Zayandeh-Rud Basin in 2002, 2009, and 2015 from Isfahan Water and Sewerage Organization. Correlation analysis is then conducted to investigate the effect of land use changes on water quality at different spatial scales. Land use analysis in the entire basin shows that despite an increase in urban and agricultural lands from 2002 to 2015, bare lands, vegetation, and water covers have had a decreasing trend. Moreover, various land uses at different scales show some correlation with water quality parameters. The strongest correlations in this study belong to sub-basin scale. Therefore, it is recommended to use this spatial scale to investigate the relation between land use and water quality parameters

Particulate Matter (PM₂.₅) pollution in China has been a primary concern for public health in recent years, which requires banks to appropriately control their credit supply to industries with high pollution, high energy consumption, and surplus capacity. For this reason, this paper examines economic determinants of PM₂.₅ concentrations and incorporates the spatial spillover effect of bank credit by employing the spatial Durbin model (SDM) under the stochastic impacts by regression on population, affluence and technology framework. Using China's provincial dataset from 1998 to 2016, the main findings are as follows: First, there is evidence in support of spatial dependence of PM₂.₅ concentrations and their inverted U-shaped relationship with economic growth in China. Second, PM₂.₅ concentrations in a province tend to increase as the level of its own urbanization increases, but they decrease as its own human capital and bank credit increase. Meanwhile, the level of neighboring urbanization positively influences a province's PM₂.₅ concentrations, whereas neighboring population size, industrialization, trade openness, and bank credit present negative impacts. Third, indirect effects of the SDM indicate significant and negative spatial spillover effect of bank credit on PM₂.₅ concentrations. These findings implicate policies on reforming economic growth, urbanization, human capital and bank credit to tackle PM₂.₅ pollution in China from a cross-provincial collaboration perspective.

Public health is threatened by air pollution and high temperature, especially in urban areas and areas impacted by climate change. Well-designed urban forms have co-benefits on promoting human health and mediating atmospheric environment-related threats (e.g., high temperature and air pollution). Previous studies overlooked these mediating effects of urban form on suicide mortality. This study used partial least squares modeling and countywide data in Taiwan to identify the crucial influences and pathways of urban environment, socioeconomic status, and diseases on suicide mortality. The model considered the impact of the characteristics of urban form (i.e., urban development intensity, land mix, and urban sprawl), urban industrial status (i.e., industrial level), urban greening (i.e., green coverage), disease (i.e., important diseases morbidity of human immunodeficiency virus [HIV], cerebrovascular disease [CVD], chronic liver disease and cirrhosis [CLDC], nephritis, nephrotic syndrome and nephrosis [NNSN], malignant tumor [MT]), socioeconomic status (i.e., income level and aging population rate), and the atmospheric environment (i.e., air pollution and high temperature) on suicide mortality. Optimizing land mix and minimizing urban development intensity and urban sprawl have been found to reduce suicide mortality. The mediating effect of urban form on suicide mortality originated from air pollution and high temperature, and mediating air pollution was greater than high temperature. Furthermore, industrial level, important diseases (HIV, CVD, CLDC, NNSN, and MT) morbidity, an aging population rate, air pollution, and high temperature were associated with an increase in suicide mortality, whereas green coverage and income level were associated with a reduction in suicide rates. The findings demonstrate that appropriate urban policy and urban planning may lower suicide mortality, be useful strategies for suicide prevention, and be a foundation for building a healthy city. Moreover, this study provides clarity on the complex relationship of suicide and the urban environment while identifying crucial factors.

Rapid economic growth, industrialization, and urbanization have caused frequent air pollution events in East Asia over the last few decades. Recently, aerosol data from geostationary satellite sensors have been used to monitor ground-level particulate matter (PM) concentrations hourly. However, many studies have focused on using historical datasets to develop PM estimation models, often decreasing their predictability for unseen data in new days. To mitigate this problem, this study proposes a novel real-time learning (RTL) approach to estimate PM with aerodynamic diameters of <10 μm (PM₁₀) and <2.5 μm (PM₂.₅) using hourly aerosol data from the Geostationary Ocean Color Imager (GOCI) and numerical model outputs for daytime conditions over Northeast Asia. Three schemes with different weighting strategies were evaluated using 10-fold cross-validation (CV). The RTL models, which considered both concentration and time as weighting factors (i.e., Scheme 3) yielded consistent improvement for 10-fold CV performance on both hourly and monthly scales. The real-time calibration results for PM₁₀ and PM₂.₅ were R² = 0.97 and 0.96, and relative root mean square error (rRMSE) = 12.1% and 12.0%, respectively, and the 10-fold CV results for PM₁₀ and PM₂.₅ were R² = 0.73 and 0.69 and rRMSE = 41.8% and 39.6%, respectively. These results were superior to results from the offline models in previous studies, which were based on historical data on an hourly scale. Moreover, we estimated PM concentrations in the ocean without using land-based variables, and clearly demonstrated the PM transport over time. Because the proposed models are based on the RTL approach, the density of in-situ monitoring sites could be a major uncertainty factor. This study identified that a high error occurred in low-density areas, whereas a low error occurred in high-density areas. The proposed approach can be operated to monitor ground-level PM concentrations in real-time with uncertainty analysis to ensure optimal results.

In peri-urban critical zones, soil ecosystems are highly affected by increasing urbanization, causing probably an intense interaction between dissolved organic matter (DOM) and heavy metals in soil. Such interaction is critical for understanding the biogeochemical cycles of both organic matter and heavy metals in these zones. However, limited research has reported the correlative distribution of DOM and heavy metals at high seasonal and spatial resolutions in peri-urban critical zones. In this study, 160 soil samples were collected from the farmland and forestland of Zhangxi watershed, in Ningbo, eastern China during spring, summer, fall and winter four seasons. UV–visible absorption and fluorescent spectroscopy were used to explore the optical characteristics of DOM. The results indicated a mixture of exogenous and autogenous sources of DOM in the Zhangxi watershed, while DOM in farmland exhibited a higher degree of aromaticity and humification than that in forestland. Fluorescent results showed that humic acid-like, fulvic acid-like and microbial-derived humic-like fractions were mostly affected by seasons. The distribution of heavy metals was affected mainly by land-use changes and seasons. Correlation analysis between heavy metals and DOM characteristics and components suggested that aromatic and humic substances were more favorable in binding with EDTA extractable Ni, Cu, Zn and Cd. The bioavailable Cd and Pb decreased due to binding with humic fractions, indicating its great effects on the bioavailability of Cd and Pb. Overall, these findings provide an insight into the correlative distributions of DOM and heavy metals in peri-urban areas, thereby highlighting their biogeochemical cycling in the soil environment.

An increasing body of evidence has linked greenspace and various health outcomes in children and adolescents, but the conclusions were inconsistent. For this review, we comprehensively summarized the measurement methods of greenspace, resultant health outcomes, and potential mechanisms from epidemiological studies in children and adolescents (aged ≤19 years). We searched for studies published and indexed in MEDLINE and EMBASE (via Ovid) up to April 11, 2022. There were a total of 9,291 studies identified with 140 articles from 28 countries finally assessed and included in this systematic review. Over 70% of the studies were conducted in highly urbanised countries/regions, but very limited research has been done in low-and middle-income countries and none in Africa. Measures of greenspace varied. Various health outcomes were reported, including protective effects of greenspace exposure on aspects of obesity/overweight, myopia, lung health, circulatory health, cognitive function, and general health in children and adolescents. The associations between greenspace exposure and other health outcomes were inconsistent, especially for respiratory health studies. We pooled odds ratios (OR) using random-effects meta-analysis for health outcomes of asthma (OR = 0.94, 95%CI: 0.84 to 1.06), allergic rhinitis (OR = 0.95; 95% CI: 0.73 to 1.25), and obesity/overweight (OR = 0.91, 95%CI: 0.84 to 0.98) with per 0.1 unit increase in normalized difference in vegetation index (NDVI). These associations have important implications for the assessment and management of urban environment and health in children and adolescents.

Urbanization has destroyed river ecosystems, leading to eutrophication. Heavy metals are frequently observed in urban rivers, and the joint effects of eutrophication and heavy metals on microbial communities, especially on fungal communities, have not been adequately explored. In this study, we explored the effect of sediment physicochemical factors and heavy metals on the microbial diversity, community structure, and functions of bacterial and fungal communities from a black-odorous river in Wuhu, China. Twenty-four samples were collected, and the diversity and structure of fungal and bacterial communities were determined by high-throughput sequencing. Proteobacteria and Rozellomycota were the main phyla in the bacterial and fungal communities, respectively. The results showed different distribution patterns of bacterial and fungal communities along the river. Physicochemical factors and heavy metals exhibited different effects on microbial variation. Specifically, pH and Cr negatively affected bacterial α-diversity, whereas total phosphorus and Cr significantly affected fungal α-diversity. Variance partitioning analysis revealed that physicochemical factors explained more of the bacterial community structure than heavy metals (49.5% vs. 36.6%), with pH and total phosphorus being the dominant factors. Opposite patterns were observed for fungal community structure, with heavy metals contributing the most (48.0%). A similar influence pattern was observed for the predicted functions of the two communities. This study suggests that heavy metals in eutrophication rivers are essential factors that shift the microbial variation and should be considered in urban river evaluation and remediation.