Natural background levels and driving factors of aluminum in shallow groundwater of an urbanized delta: Insight from eliminating anthropogenic-impacted groundwaters.

Knowledge on natural background levels (NBLs) of aluminum (Al) in groundwater can accurately assess groundwater Al contamination at a regional scale. However, it has received little attention. This study used a combination of preselection and statistic methods consisting of the oxidation capacity and the boxplot iteration methods to evaluate the NBL of shallow groundwater Al in four groundwater units of the Pearl River Delta (PRD) via eliminating anthropogenic-impacted groundwaters and to discuss driving factors controlling high NBLs of Al in groundwater in this area. A total of 280 water samples were collected, and 18 physico-chemical parameters including Redox potential, dissolved oxygen, pH, total dissolved solids, HCO3 -, NH4 +, NO3 -, SO4 2-, Cl-, NO2 -, F-, K+, Na+, Ca2+, Mg2+, Fe, Mn, and Al were analyzed. Results showed that groundwater Al NBLs in groundwater units A-D were 0.11, 0.16, 0.15, and 0.08 mg/L, respectively. The used method in this study is acceptable for the assessment of groundwater Al NBLs in the PRD, because groundwater Al concentrations in various groundwater units in residual datasets were independent of land-use types, but they were opposite in the original datasets. The dissolution of Al-rich minerals in sediments/rocks was the major source for groundwater Al NBLs in the PRD, and the interaction with Al-rich river water was secondary one. The high groundwater Al NBL in groundwater unit B was mainly attributed to the acid precipitation and the organic matter mineralization inducing the release of Al in Quaternary sediments. By contrast, the high groundwater Al NBL in groundwater unit C mainly was ascribed to the release of Al complexes such as fluoroaluminate from rocks/soils into groundwater induced by acid precipitation, but it was limited by the dissolution of Mg minerals (e.g., dolomite) in aquifers. This study provides not only useful groundwater Al NBLs for the evaluation of groundwater Al contamination but also a reference for understanding the natural geochemical factors controlling groundwater Al in urbanized deltas such as the PRD. PRACTITIONER POINTS: The natural background level (NBL) of groundwater aluminum in the Pearl River Delta (PRD) was evaluated. The dissolution of aluminum-rich minerals in sediments/rocks was the major source for groundwater aluminum NBLs in the PRD. The acid precipitation and organic matter mineralization contribute to high groundwater Al NBL in the groundwater unit B. The acid precipitation contributes to high groundwater Al NBL in the groundwater unit C, while dissolution of magnesium minerals limits it.

[Meteorological Influences on Annual Variation and Trend of Autumn Surface Ozone in the Pearl River Delta].

Based on the ozone （O3） monitoring data of the Pearl River Delta （PRD） from 2015 to 2022 and the reanalysis of meteorological data, the impact of meteorological conditions on the annual variation and trends of the maximum daily 8-hour average O3 concentration （MDA8-O3） were quantified using multiple linear regression （MLR） and LMG methods. The results indicated that the MLR model constructed using meteorological parameters from individual months in autumn better simulated the variation in MDA8-O3 compared to that in the model built using meteorological parameters from the entire autumn season. The combined influence of total cloud cover, relative humidity, 2 m maximum temperature, and 850 hPa zonal wind led to a reduction of 34.1 µg·m-3 in MAD8-O3 in 2020 compared to that in 2019, with contributions of 31.3%, 45.2%, 15.8%, and 6.7%, respectively. The observed trends of MDA8-O3 in the PRD for September, October, November, and the autumn season during 2015-2022 were 7.3, 5.2, 4.8, and 5.8 µg·ï¼ˆm3·a）-1, respectively. Among these, the trends driven by meteorological factors were 3.6, 2.4, 2.4, and 3.1 µg·ï¼ˆm3·a）-1. Overall, meteorological conditions contributed 53.4% to the variations in autumn MDA8-O3 in the PRD from 2015 to 2022.

High-Resolution Spatiotemporal Modeling for PM2.5 Major Components in the Pearl River Delta and Its Implications for Epidemiological Studies.

Distinguishing the effects of different fine particulate matter components (PMCs) is crucial for mitigating their effects on human health. However, the sparse distribution of locations where PM is collected for component analysis makes it challenging to investigate the relevant health effects. This study aimed to investigate the agreement between data-fusion-enhanced exposure assessment and site monitoring data in estimating the effects of PMCs on gestational diabetes mellitus (GDM). We first improved the spatial resolution and accuracy of exposure assessment for five major PMCs (EC, OM, NO3-, NH4+, and SO42-) in the Pearl River Delta region by a data fusion model that combined inputs from multiple sources using a random forest model (10-fold cross-validation R2: 0.52 to 0.61; root mean square error: 0.55 to 2.26 µg/m3). Next, we compared the associations between exposures to PMCs during pregnancy and GDM in a hospital-based cohort of 1148 pregnant women in Heshan, China, using both site monitoring data and data-fusion model estimates. The comparative analysis showed that the data-fusion-based exposure generated stronger estimates of identifying statistical disparities. This study suggests that data-fusion-enhanced estimates can improve exposure assessment and potentially mitigate the misclassification of population exposure arising from the utilization of site monitoring data.

Sources and formation characteristics of particulate nitrate in the Pearl River Delta region of China: Insights from three-year online observations.

Nitrate (NO3-) has been identified as a key component of particulate matter (PM2.5) in China. However, there is still a lack of understanding regarding its sources and how it forms, especially in the context of high-frequency and long-term data. In this study, NO3- levels were observed on an hourly basis over an almost three-year period at an urban site in the Pearl River Delta (PRD) region, China, from January 2019 to December 2021. The results reveal an average daily NO3- concentration ranging from 0.08 µg m-3 to 61.69 µg m-3, constituting 11.9 ± 12.5 % of PM2.5. This percentage rose to as high as 57 % during pollution episodes, highlighting NO3-'s significant role in pollution formation. The ammonia-rich environment was found to be the most important factor in promoting NO3- formation. Positive Matrix Factorization (PMF) analysis indicates that the primary sources of NO3- in the PRD region were vehicle emissions (43.8 ± 21.2 %) and coal combustion (39.1 ± 21.5 %), with shipping emissions, sea salt, soil dust and industrial emissions + biomass burning following in importance. Regarding source areas, the primary contributor of vehicle emissions was predominantly from the PRD region, whereas the coal combustion, aside from local contributions, also originates from the northern region. From a long-term perspective, NO3- pollution has remained relatively stable since the summer of 2020. Concurrently, coal combustion source has shown a localization trend. These insights derived from the extensive, high-frequency observation presented in this study serve as a valuable reference for devising strategies to control NO3- and PM2.5 in the PRD region and China.

The prevalence of preterm and low birth weight infants among migrant women in the Pearl River Delta region, China: a population-based birth cohort study.

BACKGROUND: The existing literature evaluating the association between neonatal morbidity and migrant status presents contradictory results. The purpose of this study was to compare the risk of preterm birth (PTB) and low birth weight (LBW) among newborns from local and migrant women in China's Pearl River Delta (PRD) region. METHODS: In this observational population-based study, we included all live singleton deliveries from PRD region local women and migrant women. Data were sourced from the Guangdong Medical Birth Registry Information System between Jan 1, 2014, and Dec 31, 2020. Women were categorized into three groups by maternal migrant status: local women from PRD region, migrant women from Guangdong province or from other provinces. The outcome variables that were examined included two adverse birth outcomes: PTB and LBW. The association between the risk of PTB and LBW and maternal migrant status was assessed using logistic regression. RESULTS: During 2014-2020, 5,219,133 single live deliveries were recorded, corresponding 13.22% to local women and the rest to migrant women coming from Guangdong (53.51%) and other provinces (33.26%). PTB prevalence was highest among local women (5.79%), followed by migrant women from Guangdong (5.29%), and the lowest among migrants from other provinces (4.95%). This association did not change after including maternal age, infant sex, delivery mode, and birth season in the models. Compared to local women, migrant women from other provinces had a lower risk of LBW (4.00% vs. 4.98%, P < 0.001). The prevalence of PTB and LBW was higher among local women than migrants. The odds of delivery PTB and LBW were higher for women who were age ≥ 35. Among the three maternal migration groups, the age-LBW association displayed a typical U-shaped pattern, with those in the youngest (16-24 years) and oldest (≥ 35) age categories exhibiting the higher odds of delivering a LBW neonate. With respect to infant sex, the prevalence of PTB was significantly higher in males than females among the three maternal migration groups. An opposite trend was found for LBW, and the prevalence of LBW was higher in females among the three maternal migration groups. CONCLUSION: The findings of this study contribute to the understanding of the epidemiology of PTB and LBW among migrant women. Our study suggests that it is the health and robust nature of migrant mothers that predisposes them to better birth outcomes. It is important to recognize that the results of this study, while supportive of the healthy migrant effect, cannot be considered definitive without some exploration of motivation for moving and changes in lifestyle postmigration.

Spatiotemporal differences and influencing factors of urban vitality and urban expansion coupling coordination in the Pearl River Delta.

In the contemporary state of accelerated urbanization in China, urban expansion has become the mainstream trend of urban development. However, in the context of urban expansion, whether coordinated development between urban expansion and urban vitality is achieved is an important concern facing the current urban expansion process. The Pearl River Delta (PRD) urban agglomeration is a hotspot of rapid economic development in China, and it is essential to examine the coupling relationship between the region's urban dynamics and urban expansion to promote rational urban development. This study analyzes the dynamics and evolutionary characteristics of urban expansion based on multisource nighttime light data, employing an UERI and other methods. We apply the entropy method and coupling coordination model to evaluate urban vitality and conduct a coupling analysis of urban expansion and urban vitality from 1992 to 2021. The results show that during the study period, the urban built-up area of the PRD urban agglomeration increased by 61,131.59 km2, urban vitality gradually increased each year, the coupling coordination between urban vitality and urban expansion gradually increased, and factors such as economic development, urban planning, and geographical location advantages also influenced changes in urban vitality and urban expansion and their coupling and coordination in the study area. This study provides a methodological reference and data support for the investigating the spatiotemporal evolution of urban agglomerations and urban vitality analysis.

Moving together or left behind? An examination of rural migrant working mothers' childcare strategies in the cities.

BACKGROUND: In China, an increasing number of rural mothers participate in urban labour markets, but little is known about their decisions regarding childcare while living in these cities. Why do some rural mothers migrate to the cities with their children, whereas others leave their children behind in the countryside? METHODS: This study analysed 1852 samples from the 2016 China Migrant Dynamic Survey of rural migrant mothers collected in the Pearl River Delta (PRD). These mothers were registered with agricultural hukou outside of the PRD and had at least one child under 18 years of age. RESULTS: The results indicated that 57.8% of these mothers migrated together with their children. Rural migrant mothers who were self-employed, had a higher level of household income on a log10 scale and had a longer duration of migration were more willing to adopt closely performing motherhood than rural migrant mothers who were not self-employed. Additionally, rural working mothers who were intra-provincial migrants and had a smaller number of children were more likely to bring their children to the cities than rural working mothers who were inter-provincial migrants. CONCLUSIONS: This study works to strengthen the understanding of rural migrant working mothers' childcare strategies, provide insights for future policy studies and contribute to evidence-based recommendations for policymakers regarding internal rural-to-urban migration, migrant women and the wellbeing of the families of migrants.

[Prediction of Autumn Ozone Concentration in the Pearl River Delta Based on Machine Learning].

Based on the observation data of the daily maximum 8-hour ozone (O3) average concentration[MDA8-O3, ρ(O3-8h)] and meteorological reanalysis data in the Pearl River Delta Region from 2015 to 2022, four machine learning methods, i.e., support vector machine regression (SVR), random forest (RF), multi-layer perceptron (MLP), and lightweight gradient boosting machine (LG) were used to establish MDA8-O3 prediction models. The results showed that the SVR model had the best prediction performance on MDA8-O3 during the whole year, the coefficient of determination (R2) reached 0.86, and the root mean square error (RMSE) and mean absolute error (MAE) were 16.3 µg·m-3 and 12.3 µg·m-3, respectively. The prediction performance of the SVR model in autumn was still slightly better than that of LG and MLP, with R2,RMSE,and MAE values of 0.88, 19.8 µg·m-3,and 16.1 µg·m-3, respectively. The RF model performed the worst in the autumn prediction. In addition, the models trained by data from the whole year had better prediction ability on autumn MDA8-O3 than that of those only trained by autumn data, and the R2 differed 0.08-0.14.

Hybrid life-cycle and hierarchical archimedean copula analyses for identifying pathways of greenhouse gas mitigation in domestic sewage treatment systems.

Electricity consumption and anaerobic reactions cause direct and indirect greenhouse gas (GHG) emissions within domestic sewage treatment systems (DSTSs). GHG emissions in DSTSs were influenced by the sewage quantity and the efficacy of treatment technologies. To address combined effects of these variables, this study presented an approach for identifying pathways for GHG mitigation within the DSTSs of cities under climate change and socio-economic development, through combining life cycle analysis (LCA) and the Hierarchical Archimedean copula (HAC) methods. The approach was innovative in the following aspects: 1) quantifying the GHG emissions of the DSTSs; 2) identifying the correlations among temperature changes, socioeconomic development, and domestic sewage quantity, and 3) predicting the future fluctuations in GHG emissions from the DSTSs. The effectiveness of the proposed approach was validated through its application to an urban agglomeration in the Pearl River Delta (PRD), China. To identify the potentials of GHG mitigation in the DSTSs, two pathways (i.e., general and optimized) were proposed according to the different technical choices for establishing facilities from 2021 to 2030. The results indicated that GHG emissions from the DSTS in the PRD were [3.01, 4.96] Mt CO2eq in 2021, with substantial contributions from Shenzhen and Guangzhou. Moreover, GHG emissions from the sewage treatment facilities based on Anaerobic-Anoxic-Axic (AAO) technology were higher than those based on other technologies. Under the optimized pathway, GHG emissions, contributed by the technologies of Continuous Cycle Aeration System (CASS) and Oxidation Ditch (OD), were the lowest. Through the results of correlation analysis, the impact of socioeconomic development on domestic sewage quantities was more significant than that of climate change. Domestic sewage quantities in the cities of the PRD would increase by 4.10%-28.38%, 17.14%-26.01%, and 18.15%-26.50% from 2022 to 2030 under three Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5. These findings demonstrated that the capacities of domestic sewage treatment facilities in most cities of the PRD should be substantially improved from 0.12 to 2.99 times between 2022 and 2030. Under the optimized pathway, the future GHG emissions of the CASS method would be the lowest, followed by the OD method.

Ecological risk assessment of the typical anti-epidemic drugs in the Pearl River Delta by tracing their source and residual characteristics.

Since the outbreak of the COVID-19 pandemic, the anti-epidemic drugs have been used in extraordinary quantities with high intensity, and concerns have grown about their potential ecological risks due to their continued release and persistence in the receiving environments. A systematic investigation, covering the samples from hospital wastewater, effluent from wastewater treatment plants and receiving water bodies in the Pearl River Delta Region (PRDR), was carried out and aimed at tracing the sources and fate of 30 typical anti-epidemic in different water matrixes and evaluating their ecological risk. The results showed that these typical anti-epidemic drugs residues were detected in most of the sampling sites, with the highest concentration measured in hospital wastewater, whose concentrations were as high as ppb level, while the highest concentration of the surface water samples in tributaries was lower than ppb level. Anti-epidemic drugs contained in hospital wastewater and effluent from WWTPs were the main sources of drug residues in the surface water of this region. In the surface water of PRDR, although the detected concentration anti-epidemic drugs were basically in the range of 0-10 ng/L. The risk quotient of several anti-epidemic drugs, including Ciprofloxacin (CFX), Ofloxacin (OFX), Erythromycin (ETM), Clindamycin (CLI), and Sulfamethoxazole (SMX), was calculated to be a high value, which indicated that they might cause non-negligible ecological risk to the aquatic environment.

An improved approach for evaluating landscape ecological risks and exploring its coupling coordination with ecosystem services.

The rapid urbanization has accelerated the destruction of regional ecosystems, triggering ecological risks and threatening sustainable development. Landscape ecological risk (LER) evaluation is an effective tool to mitigate such negative impacts. However, the existing evaluation systems exhibit certain subjectivity. Therefore, an improved LER evaluation method was proposed, which incorporates ecosystem services (ESs) to characterize landscape vulnerability. The method was validated using the Pearl River Delta urban agglomeration (PRDUA) as the study area. The results showed that the optimal grain size and extent for landscape pattern analysis in the PRDUA were determined to be 150 m and 6km × 6 km, respectively. The comparison results with the traditional LER evaluation method demonstrated the improved method's superior rationality and reliability. The hotspot analysis based on the Getis-Ord Gi* method revealed that the hotspots of LER were mainly concentrated in the densely populated areas of the south-central region of the PRDUA. The coupling coordination degree (CCD) between LERs and ESs showed four different levels of development in both temporal and spatial dimensions, generally dominated by moderately balanced development and lagging ESs, reflecting the unbalanced ecological environment and socio-economic development of the PRDUA. It is recommended that the ecosystems in the PRDUA be managed and protected separately according to the delineated Ecological Protection Area (EPA), Urban Built-up Area (UBA), and Urban Ecological Boundary Area (UEBA). This study can provide an important reference for regional ecosystem conservation and management.

Evaluation and optimization of ecological landscape pattern for urban agglomeration in the Pearl River Delta, China.

The evaluation and optimization of landscape ecological pattern has important implications for the accurate improvement of forest quality and high-quality urban development in the Pearl River Delta urban agglomeration. Based on the "one map" data and digital elevation model data of forest resource management in 2021, we evaluated and optimized landscape ecological pattern of the Pearl River Delta urban agglomeration by morphological spatial pattern analysis and minimum cumulative resistance model. The results showed that there were 435861 patches in the Pearl River Delta urban agglomeration that could be used as ecological source area, covering an area of 7346.60 km2 and accounting for 13.4% of the Pearl River Delta area. Thirty patches were selected as the ecological source area of the study area by using the area and patch importance index, covering an area of 2792.59 km2 and accounting for 5.1% of the Pearl River Delta area. The overall natural environment of the Pearl River Delta urban agglomeration was excellent. The ecological resistance level was small. The peripheral ecological resistance was low. The core ecological resistance was high. There was still a large room for adjustment of stand types and landscape patterns, which should be optimized by adjusting the composition and spatial distribution of tree species. The ecological network of the Pearl River Delta urban agglomeration was optimized with 30 ecological sources, 103 key ecological corridors, and 95 ecological nodes. The improvement rates of the optimized probability of connectivity index and integral index of connectivity index were 297.5% and 695.1%, respectively. The optimization results could effectively connect the ecological sources and spread the ecological service functions of ecological sources.

Importance of secondary decomposition in the accurate prediction of daily-scale ozone pollution by machine learning.

Machine learning (ML) models have been proven as a reliable tool in predicting ambient pollution concentrations at various places in the world. However, their performance in predicting the maximum daily 8-h averaged ozone (MDA8 O3), the metric often used for O3 pollution assessment and management, is relatively poorer. This is largely resulted from more irregular data fluctuations of the MDA8 O3 levels governed collectively by the synoptic condition, local photochemistry, and long-range transport. In order to improve the prediction accuracy of MDA8 O3, this study developed a secondary decomposition ML model framework which coupled the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) as the primary decomposition, the variational mode decomposition (VMD) as secondary decomposition, and the gate recurrent unit (GRU) ML model. By applying this secondary decomposition model framework on MDA8 O3 prediction for the first time, we showed that the prediction accuracy of MDA8 O3 is largely improved from R2 of 0.46 and RMSE of 30.4 µg/m3 for GRU without decomposition to R2 of 0.91 and RMSE of 12.6 µg/m3 over the Pearl River Delta of China. We also found that the prediction accuracy rate of O3 pollution non-attainments, an essential indicator for initiating contingency O3 pollution control, improved greatly from 14.9 % for GRU without decomposition to 72.5 %. The performance of O3 pollution non-attainment prediction is relatively higher in southwestern PRD, which is mainly due to greater number and severity of O3 non-attainments in southwestern cities located downwind of the emission hotspot area at central PRD. This study underscored the importance of secondary decomposition in accurately predicting daily-scale O3 concentration and non-attainments over the PRD, which can be extended to other photochemically active region worldwide to improve their O3 prediction accuracy and assist in O3 contingency control.

Maximizing ozone control by spatial sensitivity-oriented mitigation strategy in the Pearl River Delta Region, China.

The Pearl River Delta (PRD) has long been plagued by severe O3 pollution, particularly during the autumn. A regional O3 pollution episode influenced by the Western Pacific Subtropical High in September 2021 was characterized by near-surface O3 escalation due to strong photochemical reactions within the planetary boundary layer. This event was targeted to develop effective control strategies through investigation of precursor control type and scope based on the high-order decoupled direct method (HDDM) and integrated source apportionment method (ISAM) of CMAQ. Generally, the majority of areas (67.0 %) were under NOx-limited regime, which should strengthen afternoon NOx control inferred by positive convex O3 responses. However, high emission and heavily polluted areas located in central PRD were under VOC-limited regime (11.6 %) or mixed regime (15.0 %). The remaining areas (6.4 %) were under NOx-titration or insensitive conditions. Regarding source apportionment, Guangdong province contributed 32.3 %-58.4 % to MDA8 O3 of PRD, especially higher proportion (>50 %) to central areas. Overall, local-focused NOx/VOC emission reductions had limited effects on O3 mitigation for receptor cities compared to regional-cooperative regulation. When region-wide VOC emission reduction was implemented, MDA8 O3 in VOC-limited grids exhibited the largest declines (2.3 %-4.1 %, 3.9- 7.0 µg·m-3). However, unified NOx control contributed to increasing MDA8 O3 in VOC-limited grids (most stations located for air quality evaluation) whereas decreased MDA8 O3 by 2.1 %- 5.7 %, 3.0- 8.2 µg·m-3 in large-scale NOx-limited grids. The sensitivity-oriented regional control avoided O3 rebound and achieved the greatest decline of 3.4 %- 5.0 %, 5.7- 8.4 µg·m-3 in VOC-limited grids; additionally, time-refined dynamic aggressive NOx control decreased peak O3 by an extra 1.2- 6 µg·m-3, both of which facilitate the regulation for the forecasting O3 episodes. These findings suggest that in heavily polluted environments, the enhancement of O3 regulation benefits requires meticulous, coordinated, and dynamic NOx and VOC controls spanning the entire region based on high-resolution analysis of heterogeneous O3-NOx-VOC sensitivity. Furthermore, emission reduction gains should be more reasonably reflected through increasing in-situ observations covering multi-sensitivity regions.

Spatio-temporal dynamics and sensitive distance of nighttime light environment in Pearl River Delta Protected Areas, China.

Protected areas (PAs) are important barriers to ensure the ecological security of territory. Light pollution is a threat to PAs, which is particularly obvious in the urban agglomeration environment. We used multi-source big data (satellite remote sensing light data, land cover types and points of interest) to quantitatively analyze the temporal and spatial dynamics of nighttime light in the PAs of the Pearl River Delta (PRD) urban agglomeration from 2000 to 2018, the correlation between the night light environment within the PAs and human activity intensity outside, as well as the sensitive distance of the PAs to artificial light interference. The results showed that the total value of nighttime light data of PAs in the PRD increased from 71107 nanoW·cm-2·sr-1 to 127682 nanoW·cm-2·sr-1 from 2000 to 2018, the mean value per pixel increased from 15.3 nanoW·cm-2·sr-1 to 23.7 nanoW·cm-2·sr-1, and the lighted ratio increased from 73.3% to 86.4%, indicating that the nighttime light environment of PAs in the region were facing cumulative deterioration risks and serious challenges. The nighttime light intensity of the PAs in the core area of the PRD was much higher than that in the peripheral areas such as Zhaoqing and Huizhou, whereas the expansion degree of the PAs in the peripheral areas was higher than that in the core area. The nighttime light environment inside the PAs was positively correlated with the intensity of human activities around it. The most sensitive distance of the PAs to the artificial light interference around it was 10 km, and the interference degree tended to be stable after 30 km. We proposed that 0-10 km area outside the boundary of the PAs should be the light control core zone and 10-20 km area as the control buffer zone.

Dynamic simulation of carbon emission under different policy scenarios in Pearl River Delta urban agglomeration, China.

Global climate continues to warm; by reducing carbon emission (CE) to cope with climate warming has become a global consensus. The influencing factors of CE exhibit diversification and spatial characteristics, and the complexity of the CE system poses challenges to green and low-carbon development and the realization of China's dual-carbon goals. Taking the Pearl River Delta urban agglomeration as an example, this study explored the influencing factors of CE and designed emission reduction schemes with the help of multi-scale geographically weighted regression (MGWR). Based on this, the system dynamics model was used to construct a CE system framework considering multi-dimensional driving factors, so as to combine the complex CE system with the emission reduction countermeasures considering spatial heterogeneity, and realize the dynamic simulation of CE reduction policies. The results showed that the urban agglomeration as a whole will reach carbon peak by 2025. Shenzhen, Zhuhai, and Dongguan have achieved carbon peak before 2020, while other cities will reach carbon peak by 2025-2030. The government policy constraints can effectively curb CE, but if government constraints were relaxed, CE will rise and individual cities will not reach carbon peak. Comprehensive CE reduction policies are better than a single CE reduction policy. The study found that this model framework provides a systematic analysis of carbon reduction strategies for urban agglomerations, offering decision-makers various combinations of economic development and green low-carbon objectives. This will further contribute to a multi-faceted mitigation of high emission in urban agglomeration and promote regional sustainable development.

Distribution of potentially toxic elements in soils and sediments in Pearl River Delta, China: Natural versus anthropogenic source discrimination.

Although anthropogenic contamination has been regarded as the most important source of potentially toxic elements (PTEs) in soils of large river delta plains, the extent to which human activities affect PTEs in soils is worth exploring. This study used high density geochemical data to distinguish source patterns of PTEs in soils of the Pearl River Delta Economic Zone, a large industrialized and urbanized area in China. Enrichment factor, discriminant analysis, principal components analysis, cumulative distribution function, and positive matrix factorization were used to identify sources of PTEs in soils. The results indicated that parent material was the most significant factor affecting geochemical characteristics of PTEs in soils. Median concentrations of Cd, Cr, Cu, Hg, Pb, and Zn were 0.400, 88.5, 40.5, 0.143, 43.0, and 116.0 mg/kg for stream sediments, 0.333, 75.7, 39.0, 0.121, 42.6, and 98.5 mg/kg for deep soils, and 0.365, 74.0, 45.1, 0.143, 44.6, and 119.5 mg/kg for surface soils, respectively, all of which exceed relevant reference standards. Compared with stream sediments and deep soils, surface soils exhibit substantial concentrations of PTEs. Chemical weathering and erosion of parent materials distributed in the Pearl River Delta were the main sources of PTEs in soils. Diffuse contamination and many small local contamination sources distributed throughout the study area were the most significant anthropogenic sources of PTEs in surface soils. Intensive human activities failed to change the soil geochemical characteristics derived from the parent material at the regional scale. However, it could induce non-point source pollution and local severe PTEs pollution in surface soils.

Per- and polyfluoroalkyl substances in ambient fine particulate matter in the Pearl River Delta, China: Levels, distribution and health implications.

Per- and polyfluoroalkyl substances (PFAS) have attracted worldwide attention as one of persistent organic pollutants; however, there is limited knowledge about the exposure concentrations of PFAS-contained ambient particulate matter and the related health risks. This study investigated the abundance and distribution of 32 PFAS in fine particulate matter (PM2.5) collected from 93 primary or secondary schools across the Pearl River Delta region (PRD), China. These chemicals comprise four PFAS categories which includes perfluoroalkyl carboxylic acids (PFCAs), perfluoroalkyl sulfonic acids (PFSAs), perfluoroalkyl acid (PFAA) precursors and PFAS alternatives. In general, concentrations of target PFAS ranged from 11.52 to 419.72 pg/m3 (median: 57.29 pg/m3) across sites. By categories, concentrations of PFSAs (median: 26.05 pg/m3) were the dominant PFAS categories, followed by PFCAs (14.25 pg/m3), PFAS alternatives (2.75 pg/m3) and PFAA precursors (1.10 pg/m3). By individual PFAS, PFOS and PFOA were the dominant PFAS, which average concentration were 24.18 pg/m3 and 6.05 pg/m3, respectively. Seasonal variation showed that the concentrations of PFCAs and PFSAs were higher in winter than in summer, whereas opposite seasonal trends were observed in PFAA precursors and PFAS alternatives. Estimated daily intake (EDI) and hazard quotient (HQ) were used to assess human inhalation-based exposure risks to PFAS. Although the health risks of PFAS via inhalation were insignificant (HQ far less than one), sufficient attention should be levied to ascertain the human exposure risks through inhalation, given that exposure to PFAS through air inhalation is a long term and cumulative process.

Key factors influencing pollution of heavy metals and phenolic compounds in mangrove sediments, South China.

Concentrations of heavy metals (HMs) and phenolic compounds with factors which potentially affected their spatial distribution were investigated in mangrove sediments, South China. Compared to Qi'ao, Futian sediments exhibited higher levels of Pb and nonylphenol (NP), but lower levels of Co and Ni. Seasonal variation showed higher concentrations of Pb, Cr, Co, NP and bisphenol A (BPA), while lower concentration of methylparaben (MP) in wet than dry season. Contaminant levels in sediments collected at different tidal heights showed insignificant variations, except for Zn and NP. MP was found negatively correlated with nearly all HMs and BPA, whereas the latter exhibited positive correlations with each other. Sedimentary total carbon, total nitrogen, C/N and N/P ratios were screened as the most influential factors affecting the distribution of these contaminants. Additionally, both salinity and total phosphate exhibited positive, while both pH and sedimentary particle size registered negative correlation, with one or more contaminants.

A vehicle-mounted dual-smog chamber: Characterization and its preliminary application to evolutionary simulation of photochemical processes in a quasi-realistic atmosphere.

Smog chambers are the effective tools for studying formation mechanisms of air pollution. Simulations by traditional smog chambers differ to a large extent from real atmospheric conditions, including light, temperature and atmospheric composition. However, the existing parameters for mechanism interpretation are derived from the traditional smog chambers. To address the gap between the traditional laboratory simulations and the photochemistry in the real atmosphere, a vehicle-mounted indoor-outdoor dual-smog chamber (JNU-VMDSC) was developed, which can be quickly transferred to the desired sites to simulate quasi-realistic atmosphere simultaneously in both chambers using "local air". Multiple key parameters of the smog chamber were characterized in the study, demonstrating that JNU-VMDSC meets the requirements of general atmospheric chemistry simulation studies. Additionally, the preliminary results for the photochemical simulations of quasi-realistic atmospheres in Pearl River Delta region and Nanling Mountains are consistent with literature reports on the photochemistry in this region. JNU-VMDSC provides a convenient and reliable experimental device and means to study the mechanism of atmospheric photochemical reactions to obtain near-real results, and will make a great contribution to the control of composite air pollution.