Generating synthetic population for simulating the spatiotemporal dynamics of epidemics.

Agent-based models have gained traction in exploring the intricate processes governing the spread of infectious diseases, particularly due to their proficiency in capturing nonlinear interaction dynamics. The fidelity of agent-based models in replicating real-world epidemic scenarios hinges on the accurate portrayal of both population-wide and individual-level interactions. In situations where comprehensive population data are lacking, synthetic populations serve as a vital input to agent-based models, approximating real-world demographic structures. While some current population synthesizers consider the structural relationships among agents from the same household, there remains room for refinement in this domain, which could potentially introduce biases in subsequent disease transmission simulations. In response, this study unveils a novel methodology for generating synthetic populations tailored for infectious disease transmission simulations. By integrating insights from microsample-derived household structures, we employ a heuristic combinatorial optimizer to recalibrate these structures, subsequently yielding synthetic populations that faithfully represent agent structural relationships. Implementing this technique, we successfully generated a spatially-explicit synthetic population encompassing over 17 million agents for Shenzhen, China. The findings affirm the method's efficacy in delineating the inherent statistical structural relationship patterns, aligning well with demographic benchmarks at both city and subzone tiers. Moreover, when assessed against a stochastic agent-based Susceptible-Exposed-Infectious-Recovered model, our results pinpointed that variations in population synthesizers can notably alter epidemic projections, influencing both the peak incidence rate and its onset.

Impacts of poverty eradication on carbon neutrality in China.

China is facing challenges to tackle the threat of climate change while reducing social inequality. Poverty eradication requires improvement in the living conditions of low-income households, which leads in turn to higher carbon footprints and may undermine the efforts of climate change mitigation. Previous studies have assessed the climate impacts of poverty eradication, but few have quantified how the additional carbon emissions of poverty eradication are shared at the subnational level in China and the impact on China's climate targets. We investigated the recent trend of carbon footprint inequality in China's provinces and estimated the climate burden of different poverty reduction schemes, measured by increased carbon emissions. The results indicate that poverty eradication will not impede the achievement of national climate targets, with an average annual household carbon footprint increase of 0.1%-1.2%. However, the carbon emissions growth in less developed provinces can be 4.0%, five times that in wealthy regions. Less developed regions suffer a greater climate burden because of poverty eradication, which may offset carbon reduction efforts. Therefore, interregional collaboration is needed to coordinate inequality reduction with investments in low-carbon trajectories in all provinces.

Assessing Transboundary Impacts of Energy-Driven Water Footprint on Scarce Water Resources in China: Catchments under Stress and Mitigation Options.

The energy supply chains operating beyond a region's jurisdiction can exert pressure on the availability of water resources in the local area. In China, however, there is a lack of transboundary assessments that investigate the effects of energy consumption on water stress within and across river basins. In this study, we therefore investigate transboundary impacts on scarce water resources that are induced by energy demands (i.e., electricity, petroleum, coal mining, oil and gas extraction, and gas production). We develop a bottom-up high spatial resolution water inventory and link it to a 2017 multiregional input-output (MRIO) table of China to analyze supply chain scarce water use at provincial and river basin levels. We find that the energy-driven water footprint accounts for 21.6% of national water usage, of which 35.7% is scarce water. Nonelectric power energy sectors contribute to around half of the nation's scarce water transfer. We identify three sets of catchments whose water resources are stressed by energy demand, i.e., (a) from the northern Hai River Basin to the eastern part of the Yellow River Basin and the Huai River Basin, (b) the northern area of the Northwest Rivers, and (c) the developed coastal city clusters in the Yangtze River Basin and the Pearl River Basin. We then evaluate the impacts of eight mitigation options, which may potentially shift around half of the moderate- or high-stress areas in the Hai River Basin and the Northwest Rivers to low to moderate (or even low) stress. We highlight the need for transboundary collaboration to sustain water-constrained energy demand and to develop targeted measures to mitigate stress on water resources within a river basin.

Air pollution control or economic development? Empirical evidence from enterprises with production restrictions.

Production restriction is an environmental regulation adopted in China to curb the air pollution of industrial enterprises. Frequent production restrictions may cause economic losses for enterprises and further hinder their green transformation. Polluting enterprises are faced with the dilemma of choosing environmental protection or economic development. Using panel data on industrial enterprises in China from 2016 to 2019, this paper evaluates the impact of production restrictions on both enterprises' environmental and economic performance with regression models. The results show that production restrictions significantly drop the concentrations of SO2 and NOx emitted from polluting enterprises. Meanwhile, production restrictions have significant negative effects on operating income, financial expenses, net profit, and environmental protection investment. The mechanism analysis reveals that production restrictions mitigate air pollutant concentrations by increasing the number of green patents and improving total factor productivity, which also verifies the Porter hypothesis. However, there is a masking mediating effect of environmental investment, which indicates that the reduction of environmental investment hinders the enterprise's efforts to control air pollution. In addition, heterogeneous analysis shows that the economic shock on microenterprises is larger than that on small enterprises. Implementing production restrictions for microenterprises may be a way to eliminate their backwards production capacity.

Air Pollutant Emission Inventory of Waste-to-Energy Plants in China and Prediction by the Artificial Neural Network Approach.

The waste-to-energy (WTE) plant has been deployed in 205 cities in China. However, it always faces public resistance to be built because of the great concerns on flue gas pollutants (FGPs). There are limited studies on the socioeconomic heterogeneity analysis and prediction models of WTE capacity/ FGP emission inventories (EIs) based on big data. In this study, the incinerator level emission factors (EFs) in 2020 of PM, SO2, NOx, CO, HCl, dioxins, Hg, Cd + Tl, and Sb + As+ Pb + Cr + Co + Cu + Mn + Ni were calculated based on 322,926 monitoring values of all the 481 WTE plants (1140 processing lines) operating in China, with uncertainties in the range of ±34.70%. The EFs were significantly 45-96% lower than the national standard (GB18485-2014) and had negative relationships with local socioeconomic elements, while WTE capacity and FGP EIs had significantly positive correlations. Gross domestic product, area of built district, and municipal solid waste generation were the main driving forces of WTE capacity. The WTE capacity increased by 150% from 2015 to 2020, while the total emission of PM, SO2, CO, dioxins, Hg, and Sb + As + Pb + Cr + Co + Cu + Mn + Ni decreased by 42.46-88.24%. The artificial neural network models were established to predict WTE capacity and FGP EIs in the city level, with the mean square errors ranging from 0.003 to 0.19 within the model validation limits. This study provides data and model support for the formulation of appropriate WTE plans and a pollutant emission control scheme in different economic regions.

Relocating Industrial Plants Delivers Win-Win Emission Reduction Benefits to Origin and Destination Regions.

Relocating pollution-intensive factories is one of the most effective measures to meet mandatory environmental regulations in developed cities while simultaneously imposing environmental pressure on the receiving cities. Existing studies often assume that relocated plants produce the same or higher emissions when relocated. However, the current pollution mitigation policies enforce even higher emission standards in the destination after plant relocation. We employ a bottom-up pollution accounting approach to assess the impact of intraregional or interregional relocation of iron and steel plants in China's Beijing-Tianjin-Hebei (BTH) area on various air pollutants; specifically, seven policy scenarios are modeled, based on stringency, implementation scope, and production technologies. We find that relocation combined with emission standards enforcement and shifts from BOF (basic oxygen furnace) to EAF (electric arc furnace) production technology may significantly reduce emissions within and outside BTH areas by as much as 28.8% compared to business as usual. The observed reduction is mainly due to the requirement of meeting ultralow emission standards directly or indirectly after relocation. Both origin and destination cities benefit from the relocation, with limited emission spillovers (+9.1%) for destinations outside BTH and even a net reduction (9.4%) in Tangshan. We conclude that combining factory relocation with stricter emission standards and production technological innovation could circumvent the Pollution Haven Hypothesis and deliver win-win air pollution reduction benefits for both origins and destinations.

Green recovery or pollution rebound? Evidence from air pollution of China in the post-COVID-19 era.

Under the strict control measures, China has achieved phased victory in combating with the COVID-19, production activities have gradually returned to normal. This paper examined whether air pollution was rebounded or realized green recovery in the post-COVID-19 era with a dataset of weather normalized pollutant concentrations using difference-in-differences models. Results showed that air pollution experienced a significant decline due to the wide range of control measures. With entering the post-epidemic period, air pollution raised due to the orderly production resumption. Specifically, production resumption increased the PM2.5 concentrations of lockdown cities and non-lockdown cities by 43.2% (22.3 µg/m3) and 35.9% (17.3 µg/m3) compared with that in the period of COVID-19 breakout. Although the economic activities of China have been gradually recovered, PM2.5 concentrations were 8.8-11.2 µg/m3 lower than the level of pre-epidemic period. In addition, the environmental effects varied across cities. With the process of production resumption, the PM2.5 concentrations of cities with higher GDP, higher secondary industry output, more private cars and higher export volume rebounded less. Most developed cities realized green recovery by economy growth and air quality improvement, such as Beijing and Shanghai. While cities with heavy industry reflected pollution rebound with slow economy recovery, such as Shenyang and Harbin. Understanding the environmental effects of control measure and production resumption can provide crucial information for developing epidemic recovery policies and dealing with pollution issues for both China and other countries.

A Novel Four Genes of Prognostic Signature for Uveal Melanoma.

Autophagy and immunity play critical roles in various cancers, but the prognostic impact of autophagy and immunity for uveal melanoma (UM) remains lacking. Therefore, the RNA sequencing of data in the TCGA-UVM dataset was downloaded from UCSC Xena database. The prognostic autophagy- and immunity-related genes (AIRGs) were selected via univariate Cox regression. Next, we applied LASSO method to construct four genes of signature in the TCGA-UVM and verified in another two GEO datasets (GSE84976 and GSE22138). This signature intimately associated with overall survival (OS) time and metastasis-free survival (MFS) time of UM, which could be considered as a prognostic indicator. Besides, by applying risk assessment, the patients of UM can be divided into two subgroups (high/low risk) with different survival time, distinct clinical outcomes, and immune microenvironments. Gene set enrichment analysis (GSEA) manifested that cancer hallmark epithelial-mesenchymal transition and KRAS pathways were positively activated in the high-risk group. Moreover, the high-risk group could be more sensitive to chemotherapies than the low-risk group. Thus, our finding suggested that the four genes of signature closely linked with UM risk and survival can afford more accurate survival prediction and potential therapeutic targets for clinical application.

Does travel closer to TOD have lower CO2 emissions? Evidence from ride-hailing in Chengdu, China.

Despite contributions to reducing private car dependency and carbon emissions, impacts of transit-oriented development (TOD) on ride-hailing usage are largely overlooked in existing studies. Using massive ride-hailing trips data in Chengdu, the influence of subway proximity on vehicle kilometers traveled (VKT) and corresponding CO2 emissions of ride-hailing is examined at the disaggregated level. Similarly, moderated multiple regression is adopted to investigate the interaction effects of subway proximity at pick-up and drop-off on VKT of ride-hailing. Results suggest that for each additional kilometer in subway proximity at pick-up/drop-off position, the VKT of ride-hailing trips is reduced by 0.315 km/0.273 km, resulting in the CO2 emission reduction of 0.063 kg/0.055 kg. Moreover, the influence of pick-up proximity on VKT change is negatively moderated by drop-off proximity and vice versa. Our results suggest that the carbon emission reduction can benefit from "T (Transit)" however the problem of regional imbalances in "D (Development)" needs to be addressed.

Machine Learning Analysis of Immune Cells for Diagnosis and Prognosis of Cutaneous Melanoma.

Tumor infiltration, known to associate with various cancer initiations and progressions, is a promising therapeutic target for aggressive cutaneous melanoma. Then, the relative infiltration of 24 kinds of immune cells in melanoma was assessed by a single sample gene set enrichment analysis (ssGSEA) program from a public database. The multiple machine learning algorithms were applied to evaluate the efficiency of immune cells in diagnosing and predicting the prognosis of melanoma. In comparison with the expression of immune cell in tumor and normal control, we built the immune diagnostic models in training dataset, which can accurately classify melanoma patients from normal (LR AUC = 0.965, RF AUC = 0.99, SVM AUC = 0.963, LASSO AUC = 0.964, and NNET AUC = 0.989). These diagnostic models were also validated in three outside datasets and suggested over 90% AUC to distinguish melanomas from normal patients. Moreover, we also developed a robust immune cell biomarker that could estimate the prognosis of melanoma. This biomarker was also further validated in internal and external datasets. Following that, we created a nomogram with a composition of risk score and clinical parameters, which had high accuracies in predicting survival over three and five years. The nomogram's decision curve revealed a bigger net benefit than the tumor stage. Furthermore, a risk score system was used to categorize melanoma patients into high- and low-risk subgroups. The high-risk group has a significantly lower life expectancy than the low-risk subgroup. Finally, we observed that complement, epithelial-mesenchymal transition, and inflammatory response were significantly activated in the high-risk group. Therefore, the findings provide new insights for understanding the tumor infiltration relevant to clinical applications as a diagnostic or prognostic biomarker for melanoma.

Effects of the joint prevention and control of atmospheric pollution policy on air pollutants-A quantitative analysis of Chinese policy texts.

Joint prevention and control of atmospheric pollution (JPCAP) policies play a vital role in alleviating regional pollution. Based on Latent Dirichlet Allocation (LDA) model, we construct two policy strength measures of effectiveness and number, and investigate the effects of policy strength on air pollutant emissions for four types of JPCAP policies. The results show that the effects of economic incentive policy tools and supporting policy tools on emission reduction deviate significantly from policy preferences. Economic incentive policy tools are the most effective in promoting emission reductions in SO2, NOx and dust, but their effectiveness are the lowest in reality. Supporting policy tools, with the highest strength, have little effect on emission reduction. Command-control policies and persuasion policies are both relatively high in quantity and effectiveness. In addition, policy strength plays a more important role in reducing air pollutants in key regions than in non-key regions. JPCAP policies have gradually changed from a single policy tool to multiple policy tools, and the government shifted its attention to improving the legal effectiveness of policies after 2015. Finally, we propose some policy implications to optimize JPCAP policies and address regional air pollution problem.

Do environmental taxes reduce air pollution? Evidence from fossil-fuel power plants in China.

Taking environmental protection into consideration, China introduced the new Environmental Protection Tax Law in 2018, which levies taxes for pollutants with higher standards. The vast majority of existing studies have investigated the impacts of environmental taxes (ETs) at the city level or province level. In contrast, we estimate their effects on pollutant reductions for fossil-fuel power plants in 30 provinces in China. Our results show that ETs have positive effects on pollutant emission reductions compared with the pollution discharge fee policy. We provide empirical evidence that sulfur dioxide (SO2), nitrogen oxide (NOx), and dust from fossil fuel power plants significantly decreased by 2.186 (7.7%), 1.550 (6.84%), and 1.064 (16.1%) tons, respectively, after the implementation of the policy. Moreover, there is an inverted U-shape relationship between pollutant emission reductions and tax rates. We offer further evidence that they play a limited role in high environmental regulation regions. Finally, we compare how different types of firms responded to ETs. The results show that ETs have limited effects on pollutant reductions for large state-owned coal power plants, which may have achieved environmental transformation to a certain extent. Therefore, policymakers could consider promoting tax rates in areas with low tax rates and strengthening tax breaks to stimulate firms to achieve pollutant reduction. In addition, local governments should set tax rates taking regional environmental regulation levels and firm heterogeneity into account.

Understanding the industrial NOx and SO2 pollutant emissions in China from sector linkage perspective.

Since the most stringent-ever clean air policy was implemented in 2013 in China, main industrial air pollutant emissions have notably decreased. However, there are few studies on air pollutant emissions of industrial sectors driven by supply chain before and after implementing this policy. This paper attempts to provide a new perspective from industrial linkage to understand the emission of air pollutants. Based on Input-Output model framework, we revealed the linkages of SO2 and NOx emissions between sectors from 2012 to 2017 and the driving forces behind emission changes. Moreover, we simulated the possible impact of the key sector linkages on air pollutant emissions. Results show that the most noteworthy change during this period is that the metal melting sector has replaced the power sector, as the largest pollutant output emission sector associated with other sectors, especially the transport equipment sector. The main reason of this phenomena is that the emission intensity reduction rate of metal smelting sector (e.g., only 17% for NOx) is far less than other sectors. In the future, the development of the equipment manufacturing may put pressure on the metal smelting sector to reduce emissions. For example, when the transport equipment sector increases total output by 20% ~ 40%, the metal smelting sector will be driven to emit 0.04Mt ~0.08Mt of NOx. This paper provides a basis to quantitatively analyze the industrial sector linkages and identify the key sectors from 2012-2017, and helps decision makers better understand the impact of sector linkage on pollutant emissions.

Spatial spillover effects of environmental regulations on air pollution: Evidence from urban agglomerations in China.

Environmental regulations affects the environmental quality of not only local areas but also surrounding regions. It remains unknown whether the effect of environmental regulations on the surrounding regions is free riding or pollution shelter. Based on the data from 2006 to 2018, the spatial correlation of PM2.5 in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations in China was examined in this study. In addition, the spatial spillover effects of environmental regulation on PM2.5 concentrations were explored while the socio-economic driving factors of the heterogeneity of pollution spillover were identified via SDM based STIRPAT framework. Results showed that the characteristics of PM2.5 concentrations spatial correlations varies from one urban agglomeration to another. This study revealed that the air pollution is affected by not only local environmental regulations, but also regulations implemented in surrounding cities. The PM2.5 concentration of BTH, YRD and PRD increased by 0.76, 0.147 and 0.109 for each unit increase in environmental regulation of surrounding cities, respectively. In fact, cities with loose regulation become the pollution shelters. The spatial spillover effects offset the improvement effects of local environmental regulations on the air quality. Furthermore, the comparison amongst three urban agglomerations showed that the spatial spillover effects of PM2.5 concentration in BTH and YRD are higher than that of PRD. This is attributed to differences in industrial structure, population density, economic development, FDI and geographical location. Therefore, the spatial spillover effects should be taken into consideration and joint regulation should be strengthened to address air pollution issues in urban aggregations.

Re-examining the embodied air pollutants in Chinese exports.

China is the world's largest exporter and may release lots of air pollutants to produce exported commodities due to taking coal as its main source of energy. Processing exports play a significant role in Chinese exports, yet previous studies of embodied air pollutants in Chinese exports failed to distinguish processing exports from normal exports. This paper investigates the effect of trade heterogeneity on the estimation of embodied emissions by re-examining the embodied air pollutants in Chinese exports based on an extended non-competitive input-output table that distinguishes processing from normal exports. The results show that processing exports generate 22.81% of the value added embodied in gross exports and 16.48% of the emissions embodied in gross exports. The embodied air pollutants in Chinese exports would be overestimated by 12%-22% without accounting for trade heterogeneity. Unequal distributions of export-related air pollutants and value added exist among different sectors. In particular, Manufacturing of Electronics and Communication Equipment sector induces 39.56% of embodied emissions in processing exports, and 41.78% of which are generated by Production and Supply of Electric Power and Steam Hot Water sector. China's restrictions on processing exports should focus not only on the direct emissions generated by each sector but also on the emissions embodied in domestic supply chains.

Can virtual water trade save water resources?

At times, certain areas of China suffering from water shortages. While China's government is spurring innovation and infrastructure to help head off such problems, it may be that some water conservation could help as well. It is well-known that water is embodied in traded goods-so called "virtual water trade" (VWT). In China, it seems that many water-poor areas are perversely engaged in VWT. Further, China is engaging in the global trend of fragmentation in production, even as an interregional phenomenon. Perhaps something could be learned about conserving or reducing VWT, if we knew where and how it is practiced. Given some proximate causes, perhaps viable policies could be formulated. To this end, we employ China's multiregional input-output tables straddling two periods to trace the trade of a given region's three types of goods: local final goods, local intermediate goods, and goods that shipped to other regions and countries. We find that goods traded interregionally in China in 2012 embodied 30.4% of all water used nationwide. Nationwide, water use increased substantially over 2007-2012 due to greater shipment volumes of water-intensive products. In fact, as suspected, the rise in value chain-related trade became a major contributing factor. Coastal areas tended to be net receivers of VWT from interior provinces, although reasons differed, e.g. Shanghai received more to fulfill final demand (67.8% of net inflow) and Zhejiang for value-chain related trade (40.2% of net inflow). In sum, the variety of our findings reveals an urgent need to consider trade types and water scarcity when developing water resource allocation and conservation policies.

A Review on Medical Image Registration as an Optimization Problem.

OBJECTIVE: In the course of clinical treatment, several medical media are required by a phy-sician in order to provide accurate and complete information about a patient. Medical image registra-tion techniques can provide a richer diagnosis and treatment information to doctors and to provide a comprehensive reference source for the researchers involved in image registration as an optimization problem. METHODS: The essence of image registration is associating two or more different images spatial asso-ciation, and getting the translation of their spatial relationship. For medical image registration, its pro-cess is not absolute. Its core purpose is finding the conversion relationship between different images. RESULT: The major step of image registration includes the change of geometrical dimensions, and change of the image of the combination, image similarity measure, iterative optimization and interpo-lation process. CONCLUSION: The contribution of this review is sort of related image registration research methods, can provide a brief reference for researchers about image registration.

Effect of Limbal relaxing incisions during implantable collamer lens surgery.

BACKGROUND: The limbal relaxing incisions (LRIs) technique is a safe and an inexpensive procedure, which is simple for experts to perform. It can effectively reduce astigmatism and result in a rapid visual rehabilitation. But there are few reports about reducing pre-existing corneal astigmatism by LRI in ICL surgery. Our research was aimed to study the effect of limbal relaxing inci sions during implantable collamer lens (ICL) surgery. METHODS: A prospective analysis reviewing consecutive cases of corneal astigmatism that had either independent ICL surgery (control group) or combined with LRIs (LRIs group). The study population consisted of 45 patients, 85 eyes, with high myopia and regular corneal astigmatism more than 0.50 diopter (D) and less than 3.00 D. The first group received ICL surgery combined with LRIs (limbal relaxing incisions); the control group received only ICL surgery alone. The outcomes considered were uncorrected distance visual acuity (UDVA), best corrected distance visual acuity (BCVA), refraction, keratometry, slit lamp biomicroscopy, indirect ophthalmoscopy, corneal topography, corneal astigmatism, endothelial cell count, and patient satisfaction. The follow-up period covered 12 months. RESULTS: The mean uncorrected distance visual acuity (UDVA) and the best corrected visual acuity (BCVA) demonstrated statistically significant improvement after surgery in both groups. At the end of the follow-up period, the UCVA was statistically better for the patients with LRIs compared with those underwent ICL surgery alone. The LRIs group showed significant reduction in the mean topographic astigmatism from 1.48 ± 0.35 D preoperatively to 0.37 ± 0.14 D postoperatively (P < .0001) after one month. The control eyes did not show a statistically significant change (P > 0.05). The mean magnitude of the surgically induced astigmatism (SIA) read 1.10 ± 0.35 D,1.13 ± 0.34D,1.13 ± 0.34D,1.11 ± 0.35D by the end of the 1st, the 3rd, the 6th and the 12th month postoperatively in LRIs group, which was slightly lower than the target-induced astigmatism (TIA). The difference in SIA between the LRI and the control group was statistically significant by the end of the 1st, the 3rd, the 6th and the 12th month postoperatively (P < 0.001). The mean correction index (CI) was less than 1, which indicated undercorrection effect of limbal relaxing incision. No difference was observed in the postoperative endothelial cell count between the two groups. There was no intraoperative and postoperative ocular or systemic complication. CONCLUSION: Limbal relaxing incision is an effective method in reducing corneal astigmatism during implantable collamer lens surgery. TRIAL REGISTRATION: The trial was retrospectively registered in 14 April 2017. (NO: ChiCTR-ONR-17011147 ).

Groundwater remediation from the past to the future: A bibliometric analysis.

Groundwater is an important component of terrestrial ecosystems and plays a role in geochemical cycling. Groundwater is also used for agricultural irrigation and for the domestic supply of drinking water in most nations. However, groundwater contamination has led to many research efforts on groundwater remediation technologies and strategies. This study evaluated a total of 5486 groundwater remediation-related publications from 1995 to 2015 using bibliometric technology and social network analysis, to provide a quantitative analysis and a global view on the current research trend and future research directions. Our results underline a strong research interest and an urgent need to remediate groundwater pollution due to the increasing number of both groundwater contamination and remediation publications. In the past two decades, the United States (U.S.) published 41.1% of the papers and it was the core country of the international collaboration network, cooperating with the other 19 most productive countries. Besides the active international collaboration, the funding agencies also played positive roles to foster the science and technology publications. With respect to the analysis of the distribution of funding agencies, the National Science Foundation of China sponsored most of the groundwater remediation research. We also identified the most productive journals, Environmental Science and Technology and Journal of Contaminant Hydrology, which published 334 and 259 scientific articles (including research articles and reviews) over the past 20 years, respectively. In addition to journal publications, a patent analysis was performed to show the impact of intellectual property protection on journal publications. Three major remediation technologies, including chemical oxidation, biodegradation and adsorption, have received increasing interest in both journal publication and patent development. Our results provide a valuable reference and global overview to identify the potential obstacles and opportunities for researchers who currently work on groundwater contamination, remediation and related topics.