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.

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.

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.

Evaluating wetland ecosystem services value and dominant functions: Insights from the Pearl River Delta.

Weakening wetland ecosystem services (ES) significantly hinders the achievement of the Sustainable Development Goals (SDGs). It is essential to combine multiple methods for evaluating wetland ecosystem services value (ESV) and to clearly depict the spatial distribution of ESVs. Based on the local conditions of the Pearl River Delta (PRD), this study proposed a monetary evaluation system for wetland ESV, developed a method for spatially allocating individual ESVs, and identified the dominant wetland functions across different cities and types of wetlands. The results yielded the following findings: (1) The wetland ESV system effectively identifies differences in ESV across cities and wetland types. The PRD's ESV increased by 23.29% between 2000 and 2020. (2) The new spatial allocation method analyzed individual ESVs to provide spatial references for improving wetland ESV. Fishery products and flood control and water storage are the two largest wetland functions in the PRD. All ESVs increased except for temperature regulation and water purification. (3) The identification and classification of dominant wetland functions provide insights into site-specific management of urban wetlands informed by ESV. These results provide a reference for assessing wetland ESV in other delta regions facing high population density and wetland degradation pressures. Understanding the role of wetland ESs in supporting the SDGs and how they interconnect and contribute to their achievement will be a key future research topic.

A novel nonlinear direct-mapping approach for multiple time scale driving force analysis of surface water quality variations under intense human interference.

Identifying the driving forces of surface water quality variations is crucial for urban environmental management, especially in densely populated regions. Statistic mapping is an approach that allows researchers to directly explore the response of surface water quality to potential drivers. Conventionally, these methods encounter a mixture of issues, including nonlinear relationships and information on multiple time-scale, caused by disparities in the influencing frequencies and degrees of driving factors. In this research, a nonlinear direct-mapping approach was developed to quantitatively analyze the driving force of surface water quality under multiple time scales. This approach separated the fluctuation and trend information from water quality data and then established a direct-mapping relationship, thereby achieving the visible multilayer structure containing both linear and nonlinear information from the time scale. Typical water pollutants including total nitrogen (TN) and total phosphorus (TP) in the Pearl River Delta (PRD), were used to verify the methodology and compare its ability to analyze driving forces with traditional statistic approaches. The results demonstrated that this approach could establish a visual multilayer mapping structure with strong interpretability, which effectively captured the contained nonlinear information, thus improving the fitting degree by 12.43% compared with traditional methods. Moreover, it successfully identified the dominant driving forces of TN and TP in the PRD as human activities related to NO2 and PM and natural factors. Its application in the changing environment demonstrated a potentially increased risk of TP in the PRD under multiple scenarios. Overall, this approach could serve as a reliable reference for pollution early warning in the short term and for industrial structure adjustment planning in the long term.

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.

Regional Distribution of Atmospheric Organophosphate Tri-/Diesters in the Pearl River Delta: Possible Emission, Photo-degradation, and Atmospheric Transportation.

The regional characteristics of atmospheric organophosphate triesters (OPEs) and organophosphate diesters (Di-OPs) in the Pearl River Delta (PRD) were investigated by passive air samplers mounting quartz fiber filters. The analytes were found on a regional scale. Atmospheric OPEs, semi-quantified using sampling rates of particulate-bonded PAHs, were in the range of 537-2852 pg/m3 in spring and in the range of 106-2055 pg/m3 in summer, with tris(2-chloroethyl)phosphate (TCEP) and tris(2-chloroisopropyl)phosphate as the main components. While atmospheric Di-OPs were semi-quantified using sampling rates of SO42-, in the range of 22.5-5576 pg/m3 in spring and in the range of 66.9-1019 pg/m3 in summer, with di-n-butyl phosphate and diphenyl phosphate (DPHP) being the main Di-OPs. Our results indicated that OPEs were mainly distributed in the central part of the region, which might be ascribed to the distribution of industry related to OPE-containing products. In contrast, Di-OPs were scattered in the PRD, suggesting local emission from their direct industrial application. Significantly lower levels of TCEP, triphenyl phosphate (TPHP), and DPHP were detected in summer than in spring, implying that these compounds might be partitioned off particles as the temperature increased and due to possible photo-transformation of TPHP and DPHP. The results also suggested the long-distance atmospheric transportation potential of Di-OPs.

The characteristics of nitrogen and phosphorus output in China's highly urbanized Pearl River Delta region.

The nitrogen (N) and phosphorus (P) transportation due to the anthropogenic activities have strong correlations to the water pollution events. In the highly urbanized Pearl River Delta (PRD) region of China, the main input pathways for N and P have been changed. However, their main output pathways have not yet been understood. Based on the modified export coefficient model (ECM), we have quantified the N and P outputs and identified the main factors affecting the N and P outputs in highly urbanized areas such as PRD. The results showed that the N output intensity of the PRD has increased from 3010 to 3970 kg km-2·a-1 from 2008 to 2016. The P output exhibited a similar trend, from 549 to 769 kg km-2·a-1. In terms of spatial distribution, the output intensity gradually increased from economically underdeveloped regions to economically developed regions. N and P emissions in urban wastewater increased significantly with increasing urbanization rates, with output intensities increasing by 640 kg km-2·a-1 and 141 kg km-2·a-1 from 2008 to 2016, respectively. The correlation analysis showed that population density and urbanization rate were the most relevant factors with N and P outputs intensity in highly urbanized areas. This indicates that improving the effluent standards and utilization rates of wastewater treatment plants in these regions are effective measures to control N and P output. Our findings provide some new theoretical basis for the identification and management of pollution sources in highly urbanized areas for other regions, especially developing countries.

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.

Distribution characteristics of photoinitiators and their flux estimation from the Pearl River Delta to the coastal waters of the South China Sea.

Photoinitiators (PIs) are widely used in industrial polymerization processes. It has been reported that PIs are ubiquitous in indoor environments and that humans are exposed to PIs, but the occurrence of PIs in natural environments are rarely known. In the present study, 25 PIs, including 9 benzophenones (BZPs), 8 amine co-initiators (ACIs), 4 thioxanthones (TXs) and 4 phosphine oxides (POs), were analyzed in water and sediment samples collected from eight riverine outlets of the Pearl River Delta (PRD). Eighteen, 14, and 14 of the 25 target PIs were detected in water, suspended particulate matter (SPM) and sediment samples, respectively. The total concentrations of PIs in water, SPM, and sediment were in the ranges of 2.88‒96.1 ng/L, 9.25‒923 ng/g dry weight (dw), and 3.79‒56.9 ng/g dw, with geometric mean concentration (GM) of 10.8 ng/L, 48.6 ng/g dw, and 17.1 ng/g dw, respectively. A significant linear regression was observed between the log partitioning coefficients (Kd) values of PIs and their log octanol water partition coefficient (Kow) values (R2 = 0.535, p < 0.05). The annual riverine input of PIs to the coastal waters of the South China Sea via eight main outlets of the PRD was estimated to be 4.12 × 103 kg/year, and the ∑BZPs, ∑ACIs, ∑TXs and ∑POs contributed to 1.96 × 103, 1.24 × 103, 89.6 and 830 kg/year, respectively. This is the first report of a systematic description of the occurrence characteristics of PIs exposure in water, SPM, and sediment. The environmental fate and risks of PIs in aquatic environments need further investigations.

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.

Accelerated toluene degradation over forests around megacities in southern China.

Toluene is a typical anthropogenic pollutant that has profound impacts on air quality, climate change, and human health, but its sources and sinks over forests surrounding megacities remain unclear. The Nanling Mountains (NM) is a large subtropical forest and is adjacent to the Pearl River Delta (PRD) region, a well-known hotspot for toluene emissions in southern China. However, unexpectedly low toluene concentrations (0.16 ± 0.20 ppbv) were observed at a mountaintop site in NM during a typical photochemical period. A backward trajectory analysis categorized air masses received at the site into three groups, namely, air masses from the PRD, those from central China, and from clean areas. The results revealed more abundant toluene and its key oxidation products, for example, benzaldehyde in air masses mixed with urban plumes from the PRD. Furthermore, a more than three times faster degradation rate of toluene was found in this category of air masses, indicating more photochemical consumption in NM under PRD outflow disturbance. Compared to the categorized clean and central China plumes, the simulated OH peak level in the PRD plumes (15.8 ± 2.2 × 106 molecule cm-3) increased by approximately 30% and 55%, respectively, and was significantly higher than the reported values at other background sites worldwide. The degradation of toluene in the PRD plumes was most likely accelerated by increased atmospheric oxidative capacity, which was supported by isoprene ozonolysis reactions. Our results indicate that receptor forests around megacities are not only highly polluted by urban plumes, but also play key roles in environmental safety by accelerating the degradation rate of anthropogenic pollutants.

Refined Carbon Emission Measurement Based on NPP-VIIRS Nighttime Light Data: A Case Study of the Pearl River Delta Region, China.

The accurate measurement of CO2 emissions is helpful for realizing the goals of "carbon neutralization" and "carbon peak". However, most current research on CO2 emission measurements utilizes the traditional energy balance coefficient and top-down methods. The data granularity is large, and most studies are concentrated at the national, provincial, municipal, or district/county administrative unit scale. As an important part of the Guangdong-Hong Kong-Macao Greater Bay Area of China, the Pearl River Delta region has good nighttime light vitality and faces huge carbon emission pressure. Using the Pearl River Delta as the research area, this study constructed an optimized pixel-scale regression model based on NPP-VIIRS (The Visible Infrared Imaging Radiometer Suite on the Suomi National Polar-Orbiting Partnership spacecraft) nighttime light data and CO2 emissions data at the district and county levels for 2017. In addition, the spatial pattern of CO2 emissions in the Pearl River Delta was analyzed based on the predicted CO2 emission status. The results showed that the spatial pattern of CO2 emissions in the Pearl River Delta had the distinct characteristics of the "center-edge" effect, the spatial spillover effect, and high-value aggregation, which should be considered when making related social or public decisions.

Worsening ozone air pollution with reduced NOx and VOCs in the Pearl River Delta region in autumn 2019: Implications for national control policy in China.

Ozone (O3) pollution has emerged as a major air quality issue in China. Here we emphasize the great challenges in controlling O3 pollution by analyzing the recent experience of the Pearl River Delta (PRD) in southern China in reducing the autumn O3 peaks. Despite significant reductions in the concentration of O3 precursors, i.e., nitrogen oxides (NOx) and volatile organic compounds (VOCs), regional O3 pollution in the PRD was largely worse in autumn 2019 than in autumn 2018. We found that the supra-regional and regional background concentrations of O3 increased significantly in the PRD in autumn 2019 due to increased concentrations of O3 in the vast surrounding areas. We also observed slight increases in the concentrations of PRD-regionally and Guangzhou-locally produced O3. A chemical box-model analysis confirmed a slight increase in the in-situ production of O3 and revealed that increased biogenic VOCs (BVOCs) and decreased NOx levels negated the effect of significant decrease in the anthropogenic VOCs. Taken together, these aspects exacerbated O3 pollution in the PRD region in autumn 2019 relative to autumn 2018. The findings from this study highlight the strong interactions of O3 pollution over multiple regions and the need for collaborative inter-regional efforts to control O3 pollution. The experience of PRD also underlines the key role of BVOCs and the importance of science-based strategies to decrease VOCs and NOx.

The tradeoffs between food supply and demand from the perspective of ecosystem service flows: A case study in the Pearl River Delta, China.

Ecosystem service flows are a research topic of significant interest, and exploring this topic may mitigate the shortcomings related to the spatial mismatches between supply and demand in the current ecosystem services studies. The Pearl River Delta (PRD) experiences a serious spatial mismatch in ecosystem services in particular the food supply, between the supply areas (hilly areas) and demand areas (central areas). Therefore, this study focused on the PRD as a case study to analyze change trends of food supply-demand ratio (FSDR) at city level, and depict the spatial flow path within and between cities from the perspective of ecosystem service flow with different threshold distance, using an enhanced two-step floating catchment area accessibility method. The results showed that the food demand significantly exceeded the supply, the budget was 3.58 million tons and FSDR was 0.49 in 2015. There were large discrepancies in the FSDR at the city level before and after when considering the ecosystem service flows. The FSDR of cities in the central areas increased 0.1%-30%, due to the ecosystem service flow from the low hilly areas. As delivery distances increased, the size of food flow decreased within cities and increased among cities. This led to a significant decline in the population living in severe undersupplied areas (FSDR＜0.1) and oversupplied areas (FSDR＞1), and an increase in undersupplied areas (0.1＜FSDR＜0.9). Our findings indicate that local governments would benefit from enhancing connections between supply and demand areas to meet the food demand of big cities. This study offers a comprehensive and realistic understanding of the physical situation of ecosystem service consumption by human beings, and provides decision-making information for optimize land use allocation.

Identification of close relationship between large-scale circulation patterns and ozone-precursor sensitivity in the Pearl River Delta, China.

To curb the continuous deterioration of ozone (O3) pollution in China, identifying the O3-precursor sensitivity (OPS) and its driving factors is a prerequisite for formulating effective O3 pollution control measures. Traditional OPS identification methods have limitations in terms of spatiotemporal representation and timeliness; therefore, they are not appropriate for making OPS forecasts for O3 contingency control. OPS is not only influenced by local precursor emissions but is also closely related to meteorological conditions governed by large-scale circulation (LSC). In this study, a localized three-dimensional numerical modeling system was used to investigate the relationship between LSC and OPS in the Pearl River Delta (PRD) of China during September 2017, a month with continuous O3 pollution. Our results highlighted that there was a close relationship between LSC and OPS over the PRD, and the four dominant LSC patterns corresponded well to the NOx-limited, NOx-limited, VOC-limited, and transitional regimes, respectively. The clear linkage between LSC and OPS was mainly driven by the spatial heterogeneity of NOx and VOC emissions within and beyond the PRD along the prevailing winds under different LSC patterns. A conceptual model was developed to highlight the intrinsic causality between the LSC and OPS. Because current technology can accurately forecast LSC 48-72 h in advance, the LSC-based OPS forecast method provided us with a novel approach to guide contingency control and management measures to reduce peak O3 at a regional scale.

Ambient volatile organic compounds at a receptor site in the Pearl River Delta region: Variations, source apportionment and effects on ozone formation.

We present the continuously measurements of volatile organic compounds (VOCs) at a receptor site (Wan Qing Sha, WQS) in the Pearl River Delta (PRD) region from September to November of 2017. The average mixing ratios of total VOCs (TVOCs) was 36.3 ± 27.9 ppbv with the dominant contribution from alkanes (55.5%), followed by aromatics (33.3%). The diurnal variation of TVOCs showed a strong photochemical consumption during daytime, resulting in the formation of ozone (O3). Five VOC sources were resolved by the positive matrix factorization (PMF) model, including solvent usage (28.6%), liquid petroleum gas (LPG) usage (24.4%), vehicle exhaust (21.0%), industrial emissions (13.2%) and gasoline evaporation (12.9%). The regional transport air masses from the upwind cities of south China can result in the elevated concentrations of TVOCs. Low ratios of TVOCs/NOx (1.53 ± 0.88) suggested that the O3 formation regime at WQS site was VOC-limited, which also confirmed by a photochemical box model with the master chemical mechanism (PBM-MCM). Furthermore, the observation on high-O3 episode days revealed that frequent O3 outbreaks at WQS were mainly caused by the regional transport of anthropogenic VOCs especially for aromatics and the subsequent photochemical reactions. This study provides valuable information for policymakers to propose the effective control strategies on photochemical pollution in a regional perspective.

Novel Insights into Dissolved Organic Matter Processing Pathways in a Coastal Confined Aquifer System with the Highest Known Concentration of Geogenic Ammonium.

High levels of geogenic ammonium in groundwater is a highly neglected nitrogen pool in coastal aquatic systems. Although organic matter (OM) mineralization is known to significantly influence geogenic ammonium enrichment, the detailed mechanism underlying ammonium enrichment based on dissolved organic matter (DOM) characterization in coastal aquifer systems remains unclear. In this study, we characterized the optical and molecular signatures of DOM coupled with hydrogeochemistry and multiple isotopes (H/O/C/N) to elucidate in detail the mechanisms underlying the anomalously high ammonium in the coastal confined aquifer system of the Pearl River Delta, which exhibits the highest reported geogenic ammonium concentration in groundwater on the Earth. We identified three DOM fluorescent components, a marine humic-like component (C1) and two other humic-like components (C2 and C3). The autochthonous OM was first processed to the C1 component, which was further transformed to C2 and C3 components. In terms of molecular classes, the processing pathway from bacterial- or algal-derived OM to aliphatic compounds and highly unsaturated-low O compounds was identified, and highly unsaturated-low O compounds were accumulated as the main products. Compounds containing two or three N atoms were processed, and compounds with one N atom gradually accumulated, which was further degraded into CHO compounds. The ammonium (up to 179 mg/L as N) was gradually enriched due to the decomposition of CHO+3N to CHO+2N, CHO+1N, and CHO compounds. Owing to the longer residence time and less frequent fresh water flushing, the produced ammonium was retained in the aquifer as a "long-term result". The contrasting DOM characteristics, together with the differing depositional and hydrogeological conditions, give rise to the higher levels of geogenic ammonium in coastal confined aquifer systems compared with inland alluvial-lacustrine confined aquifer systems. To our knowledge, this is the first study to characterize DOM and its relationship with geogenic ammonium in coastal aquifer systems.

DDT, Chlordane, and Hexachlorobenzene in the Air of the Pearl River Delta Revisited: A Tale of Source, History, and Monsoon.

Although organochlorine pesticides (OCPs) have been banned for more than three decades, their concentrations have only decreased gradually. This may be largely attributable to their environmental persistence, illegal application, and exemption usage. This study assessed the historic and current regional context for dichlorodiphenyltrichloroethane (DDT), chlordane, and hexachlorobenzene (HCB), which were added to the Stockholm Convention in 2001. An air sampling campaign was carried out in 2018 in nine cities of the Pearl River Delta (PRD), where the historical OCP application was the most intensive in China. Different seasonalities were observed: DDT exhibited higher concentrations in summer than in winter; chlordane showed less seasonal variation, whereas HCB was higher in winter. The unique coupling of summer monsoon with DDT-infused paint usage, winter monsoon with HCB-combustion emission, and local chlordane emission jointly presents a dynamic picture of these OCPs in the PRD air. We used the BETR Global model to back-calculate annual local emissions, which accounted for insignificant contributions to the nationally documented production (<1‰). Local emissions were the main sources of p,p'-DDT and chlordane, while ocean sources were limited (<4%). This study shows that geographic-anthropogenic factors, including source, history, and air circulation pattern, combine to affect the regional fate of OCP compounds.

Towards better flood risk management: Assessing flood risk and investigating the potential mechanism based on machine learning models.

Integrating powerful machine learning models with flood risk assessment and determining the potential mechanism between risk and the driving factors are crucial for improving flood management. In this study, six machine learning models were utilized for flood risk assessment of the Pearl River Delta, in which the Gradient Boosting Decision Tree (GBDT), eXtreme Gradient Boosting (XGBoost), and Convolutional Neural Network (CNN) models were firstly applied in this field. Twelve indices were chosen and 2000 sample points were created for model training and testing. Hyperparameter optimization of the models was conducted to ensure fair comparisons. Due to uncertainty in the sample dataset, recorded inundation hot-spots were utilized to validate the rationality of the flood risk zoning maps. After determining the optimal model, the driving factors of different flood risk levels were investigated. Urban and rural areas and coastal and inland areas were also compared to determine the flood risk mechanism in different highest-risk areas. The results showed that the GBDT performed best and provided the most reasonable flood risk result among the six models. A comparison of the driving factors at different risk levels indicated that the disaster-inducing factor, disaster-breeding environment, and disaster-bearing body were not definitely becoming more serious as the flood risk increased. In the highest-risk areas, rural areas were featured by worse disaster-breeding environment than urban areas, and the disaster-inducing factors of coastal areas were more serious than those of inland areas. Moreover, the Digital Elevation Model (DEM), maximum 1-day precipitation (M1DP), and road density (RD) were the top three significant driving factors and contributed 52% to flood risk. This study not only expands the application of machine learning and deep learning methods for flood risk assessment, but also deepens our understanding of the potential mechanism of flood risk and provides insights into better flood risk management.