High-density samples are usually a prerequisite for obtaining high-precision source apportionment results in large-scale areas. In-situ field portable X-ray fluorescence spectrometry (FPXRF) is a fast and cheap way to increase the sample size of soil heavy metals (HMs). Moreover, categorical land-use types may be closely associated with source contributions. However, the above information has rarely been incorporated into the source apportionment. In this study, robust geographically weighted regression (RGWR) was first used to correct the spatially varying effect of the related soil factors (e.g., soil water and soil organic matter) on in-situ FPXRF in an urban-rural fringe of Wuhan City, China, and the correction accuracy of RGWR was compared with those of the traditionally non-spatial multiple linear regression (MLR) and basic GWR. Then, the effect of land-use types on HM concentrations was partitioned using analysis of variance (ANOVA). Last, based on the robust spatial receptor model (i.e., robust absolute principal component scores/RGWR [RAPCS/RGWR]), this study proposed RAPCS/RGWR with categorical land-use types and RGWR-corrected in-situ FPXRF data (RAPCS/RGWR_LU&FPXRF), and its performance was compared with those of RAPCS/RGWR with none or one kind of auxiliary data. Results showed that (i) the performances of the correction models for in-situ FPXRF data were in the order of RGWR > GWR > MLR, and the relative improvement of RGWR over MLR ranged from 52.6% to 70.71% for each HM; (ii) categorical land-use types significantly affected the concentrations of soil Zn, Cu, As, and Pb; (iii) the highest estimation accuracy for source contributions was obtained by RAPCS/RGWR_LU&FPXRF, and the lowest estimation accuracy was obtained by basic RAPCS/RGWR. It is concluded that land-use types and RGWR-corrected in-situ FPXRF data are closely associated with the source contribution, and RAPCS/RGWR_LU&FPXRF is a cost-effective source apportionment method for soil HMs in large-scale areas.

Effects of commercial sand mining on aquatic diversity are of increasing global concern, especially in parts of some developing countries. However, understanding of this activity on the diversity of macroinvertebrates remains focused on the α component of species diversity, rather than community functioning. Thus, there remains much uncertainty regarding how each component of taxonomic (TD) and functional (FD) diversity respond to the activity both in freshwater and marine environments. Here, we assessed the effect of sand dredging on α, β and γ components of TD and FD during different dredging periods based on the response of macroinvertebrate communities over 4 years in the second largest freshwater lake in China. After three years of active dredging, substantial reductions in each component (α, β and γ) of TD and FD were observed within the dredged area. Moreover, after one year of natural recovery, a distinct restoration was observed with an obvious return in multiple facets of TD and FD indices. No such changes were observed within the adjacent and reference areas. Decreases in the multiple components of TD and FD within the dredged area were most likely associated with the direct extraction of substrate and associated benthic fauna and indirect variations of the water and sediment environment (e.g., increases in water depth and decreases in %Clay). Furthermore, dispersal processes and mass effects mainly contributed to the maintenance of TD and FD during the dredged and recovery stages. In addition, the fast recovery of TD and FD was also related to the simple taxonomic structure and highly connected nature of the study area. Our results suggest that a more precise experimental design (BACI) should be pursued to avoid potentially confounding effects (e.g., natural disturbance) because the sensitivity of diversity indices depends upon different experimental designs. Moreover, measurement of the impacts of sand dredging on macroinvertebrate diversity can be undertaken within a rigorous framework for better understanding the patterns and processes of each component of TD and FD under the sand dredging disturbance.

Japan receives nitrogenous air pollutants via long-range transport from China. However, emissions of nitrogenous air pollutants in China have stabilized or decreased in recent years. This study examined both the long-term trends in atmospheric nitrogen (N) deposition from the 1990s to the 2010s and the response of stream water nitrate (NO₃⁻) leaching from forested areas in western Japan. A long-term (1992–2018) temporal analysis of atmospheric N deposition in Fukuoka (western Japan) was conducted. Atmospheric bulk N deposition was collected at forested sites in a suburban forest (Swₑₛₜ) and a rural forest (Rwₑₛₜ) in western Japan during 2009–2018. Stream water samples were also collected from four locations at sites Swₑₛₜ and Rwₑₛₜ during the same period. Results showed that atmospheric N deposition in Fukuoka started to decrease from the mid-2000s at an annual rate of −2.5% yr⁻¹. The decrease in atmospheric N deposition was attributable mainly to decreased atmospheric ammonium (NH₄⁺) deposition, which caused greater contribution of NO₃⁻ deposition to atmospheric N deposition. Concentrations of NO₃⁻ in the stream water samples from three of the four locations decreased significantly at an annual rate of −3.7 to −0.7% yr⁻¹. However, stream water NO₃⁻ concentrations increased in one watershed where understory vegetation has been deteriorating owing to the increased deer population. This might weaken the recovery of N leaching from forested areas.

Source apportionment can be an effective tool in mitigating soil pollution but its efficacy is often limited by a lack of information on the factors that influence the accumulation of pollutants at a site. In response to this limitation and focusing on a suite of heavy metals identified as priorities for pollution control, the study established a comprehensive pollution control framework using factor identification coupled with spatial agglomeration for agricultural soils in an industrialized part of Zhejiang Province, China. In addition to elucidating the key role of industrial and traffic activities on heavy metal accumulation through implementing a receptor model, specific influencing factors were identified using a random forest model. The distance from the soil sample location to the nearest likely industrial source was the most important factor in determining cadmium and copper concentrations, while distance to the nearest road was more important for lead and zinc pollution. Soil parent materials, pH, organic matter, and clay particle size were the key factors influencing accumulation of arsenic, chromium, and nickel. Spatial auto-correlation between levels of soil metal pollution and industrial agglomeration can enable a more targeted approach to pollution control measures. Overall, the approach and results provide a basis for improved accuracy in source apportionment, and thus improved soil pollution control, at the regional scale.

It is widely recognized that green infrastructures in urban ecosystems provides important ecosystem services, including air purification. The potential absorption of nitrogen oxides (NOₓ) by urban trees has not been fully quantified, although it is important for air pollution mitigation and the well-being of urban residents. In this study, four common tree species (Sophora japonica L., Fraxinus chinensis Roxb., Populus tomentosa Carrière, Sabina chinensis (L.)) in Beijing, China, were studied. The dual stable isotopes (¹⁵N and ¹⁸O) and a Bayesian isotope mixing model were applied to estimate the sources contributions of potential nitrogen sources to the roadside trees based on leaf and soil sampling in urban regions. The following order of sources contributions was determined: soil > dry deposition > traffic-related NOₓ. The capacity of urban trees for NOₓ removal in the city was estimated using a remote sensing and GIS approach, and the removal capacity was found to range from 0.79 to 1.11 g m⁻² a⁻¹ across administrative regions, indicating that 1304 tons of NOₓ could be potentially removed by urban trees in 2019. Our finding qualified the potential NOₓ removal by urban trees in terms of atmospheric pollution mitigation, highlighting the role of green infrastructure in air purification, which should be taken into account by stakeholders to manage green infrastructure as the basis of a nature-based approach.

Many estuaries have undergone severe saltwater intrusion in addition to simultaneously experiencing serious heavy metal pollution. To explore the effect of water density stratification associated with saltwater intrusion on the behaviour of heavy metals (Cr, Co, Ni, Cu, Zn, As, Pb, and Cd) in water and sediments, a field survey was conducted in a typical estuary (Modaomen). The content, distribution, and mobility of heavy metals were investigated, as well as the influence of environmental factors on their future. The results showed that Modaomen estuary was characterised by a notable variation in salinity along the estuary, presenting total freshwater upstream, high salinity stratification water in the mouth, and saltwater offshore. Dissolved metals presented a prominent gradient vertically, with 1.2–2.1 times higher in bottom water than in surface water and the highest contents in the highly–stratified bottom water. Elevated salinity and restricted mixing induced by water stratification were likely the causes of this outcome. The distribution of heavy metals in sediments was greatly governed by grain size, Fe/Mn (hydr)oxides, total organic carbon, salinity, and dissolved oxygen. Comprehensive evaluation, combined with total contents and chemical fractions of heavy metals, indicated that internal release from sediments contributed a considerable part to the higher levels of heavy metals in bottom water, particularly for Zn and Pb, which was fully consistent with their status in water body, and elevated salinity and lack of oxygen were likely the primary driving factors. During the phase-partition processes between bottom water and sediments, partitioning coefficients were markedly lower in the highly stratified zone, implying that saltwater intrusion facilitated the mobility and repartitioning processes of metals. Because of increased levels and toxicity of heavy metals in water and extended residence time during saltwater intrusion, the potential damage to the estuarine ecosystem should receive more attention.

Environmental lead exposure has been linked with reduced kidney function. However, evidence about its role in diabetic kidney damage, especially when considering the nutritional status of vitamin D, is sparse. In this observational study, we investigated the association between low-level lead exposure and urinary albumin-to-creatinine ratio (UACR) and assessed potential impact of vitamin D among 4033 diabetic patients in Shanghai, China. Whole blood lead was measured by graphite furnace atomic absorption spectrometry. Serum 25-hydroxyvitamin D [25(OH)D] was tested using a chemiluminescence immunoassay. The associations of blood lead with UACR and albuminuria, defined as UACR ≥30 mg/g, according to 25(OH)D levels were analyzed using linear and Poisson regression models. A doubling of blood lead level was associated with a 10.7% higher UACR (95% CI, 6.19%–15.5%) in diabetic patients with 25(OH)D < 50 nmol/L, whereas the association was attenuated toward null (2.03%; 95% CI, −5.18% to 9.78%) in those with 25(OH)D ≥ 50 nmol/L. Similarly, the risk ratios of prevalent albuminuria per doubling of blood lead level between the two groups were 1.09 (95% CI, 1.03–1.15) and 0.99 (95% CI, 0.86–1.14), respectively. Joint analysis demonstrated that a combination of high blood lead and low 25(OH)D corresponded to significantly higher UACR. Among diabetic patients with 25(OH)D < 50 nmol/L, the increment of UACR relative to blood lead was more remarkable in those with reduced estimated glomerular filtration rate (<60 mL/min/1.73 m²). These results suggested that higher blood lead levels were associated with increased urinary albumin excretion in diabetic patients with vitamin D deficiency. Further prospective studies are needed to validate our findings and to determine whether vitamin D supplementation yields a benefit.

Atmospheric peroxyacetyl nitrate (PAN) and ozone (O₃) are two typical indicators for photochemical pollution that have adverse effects on the ecosystem and human health. Observation networks for these pollutants have been expanding in developed regions of China, such as North China Plain (NCP) and Pearl River Delta (PRD), but are sparse in Yangtze River Delta (YRD), meaning their concentration and influencing factors remain poorly understood. Here, we performed a one-year measurement of atmospheric PAN, O₃, particulate matter with aerodynamic diameter smaller than 2.5 μm (PM₂.₅), nitrogen oxides (NOₓ), carbon monoxide (CO), and meteorological parameters from December 2016 to November 2017 in Shanghai. Overall, high hourly maximum PAN and O₃ were found to be 7.0 and 185 ppbv in summer, 6.2 and 146 ppbv in autumn, 5.8 and 137 ppbv in spring, and 6.0 and 76.7 ppbv in winter, respectively. Continental air masses probably carried atmospheric pollutants to the sampling site, while frequent maritime winds brought in less polluted air masses. Furthermore, positive correlations (R: 0.72–0.85) between PAN and O₃ were found in summer, indicating a predominant role of photochemistry in their formation. Unlike in summer, weak or no correlations between PAN and O₃ were featured during the other seasons, especially in winter, due to their different loss pathways. Unexpectedly, positive correlations between PAN and PM₂.₅ were found in all seasons. During summer, moderate correlation could be attributed to the strong photochemistry acting as a common driver in the formation of secondary aerosols and PAN. During winter, high PM₂.₅ might promote PAN production through HONO production, hence resulting in a good positive correlation. Additionally, the loss of PAN by thermal decomposition (TPAN) only accounted for a small fraction (ca. 1%) of the total (PAN + TPAN) during a typical winter episode, while it significantly reached 14.4 ppbv (71.1% of the total) in summer.

The Yellow River Delta (YRD) wetland, the most important estuary wetland in eastern China, has an important ecosystem service function. Rapid and intensive development has inevitably led to the accumulation of potentially toxic elements (PTEs) in soils. Therefore, identifying quantitative sources and spatial distributions of PTEs is essential for soil environmental protection in the YRD. A total of 240 topsoil samples (0–20 cm) were collected in the Yellow River Delta Nature Reserve (YRDNR) and analyzed the PTE contents. To avoid the biases of the single receptor model, positive matrix factorization, factor analysis with nonnegative constraints, and maximum likelihood principal component analysis-multivariate curve resolution-alternating least squares were used for source apportionment of soil PTEs. To promote the efficiency of multivariate geostatistical simulation, a minimum/maximum autocorrelation factor-sequential Gaussian simulation was built to map the spatial patterns of PTEs. Three factors were derived by the three receptor models, and their contributions to the source explanation were similar. As, Cr, Cu, Mn, Ni, and Zn originated from natural sources, with contributions of 85.6%–96.4 %. A total of 61.5 % of Hg was associated with atmospheric deposition of coal combustion and wastewater from upstream. Agricultural activities and oil exploitation contributed 33.5 % and 15.9 % of the Cd and Pb concentrations. Spatial distributions of soil PTEs were controlled by sedimentary grain size. A total of 47.2 % of the total study area was identified as hazardous area for Cd, 10.3 % for As, and 5.4 % for Hg. This work is expected to provide references for soil pollution assessment and management of YRDNR.

Based on the wind erosion equation and the use of moderate resolution imaging spectroradiometer (MODIS) satellite remote sensing data combined with parameter normalization processing, an optimized high spatial-temporal resolution soil fugitive dust (SFD) emission inventory compiling method was proposed in this study. The "2 + 26" cities in northern China, where heavy pollution frequently occurs, were used as a case study. Using the optimized method, we estimated that the PM₅₀, PM₁₀, and PM₂.₅ emissions from SFD of "2 + 26" cities in 2018 were 2,014,927, 1,007,463, and 151,120 tons, respectively. The dust emissions and emission factors of each city presented significant differences and were generally of a greater level in high-latitude areas (such as cities in Hebei Province) than in low-latitude areas (such as cities in Henan and Shandong Province). Moreover, with an increase in latitude, vegetation cover factors generally exhibit an upward trend, while temperature and rainfall exhibit a downward trend. The dust emissions in the different months showed significant differences. The total dust emission reached the highest level in "late winter–early spring" season (February to April), and the monthly emission accounted for 15–17% of the annual emissions. While in the "summer–autumn" season (July to November), it is the lowest level of the whole year, monthly emissions accounted for 3–5% of the annual emissions. The emission inventory method proposed in this study can provide a reference for dust emission assessment and further pollution prevention and control work.