Geohealth最新文献

{"title":"Comparison of Policy-Relevant Air Quality Metrics Calculated With Sparse In Situ Monitoring and Contiguous Satellite-Derived Data","authors":"Summer Acker,&nbsp;Tracey Holloway,&nbsp;Kevin M. Stewart,&nbsp;Aaron van Donkelaar,&nbsp;Randall V. Martin","doi":"10.1029/2025GH001586","DOIUrl":"10.1029/2025GH001586","url":null,"abstract":"<p>Compliance with the U.S. National Ambient Air Quality Standards (NAAQS) traditionally relies on a sparse network of ground-based monitors. We compare two methods for assessing whether U.S. counties are above or below the annual fine particulate matter (PM_2.5) NAAQS of 9.0 μg/m³: the monitor-based methodology used to calculate county design values (CDVs; an EPA metric representing the maximum, in-county PM_2.5 monitor value over a 3-year annual average), and a satellite-based methodology that computes county design value equivalents (CDVEs) from Washington University's global satellite-derived PM_2.5 data product. The satellite-based approach uses the 90th percentile PM_2.5 grid value in a county and shows strong overall agreement with monitor-based CDVs across 536 monitored U.S. counties (<i>r</i> = 0.76; <i>r</i>_s = 0.74). Counties were classified as aligned positives (APs), aligned negatives (ANs), non-aligned positives (NPs), or non-aligned negatives (NNs) based on whether CDVEs align or don't align with CDVs on NAAQS status. Risk factors likely contributing to larger differences between CDVEs and CDVs within non-aligned counties include ≤2 monitors, low (&lt;7 μg/m³) or high (&gt;10 μg/m³) CDVs, low (&lt;0.05%) or high (&gt;0.1%) monitor coverage, large county size, wildfires, mountains, deserts, and low urbanization. In non-aligned counties, differences grow with the number of risk factors, with seven-risk-factor counties showing 5x higher median differences than those with one. High error-risk counties cluster in the Western U.S.; low error-risk counties are in the Midwest and East. These findings highlight trade-offs between sparse and contiguous data for regulatory assessments and support integration of satellite-derived data into policy frameworks.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 7","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13339723/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148406489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying Satellite-Derived PM2.5 Data to Policy-Relevant Air Quality Metrics","authors":"Tracey Holloway,&nbsp;Summer Acker,&nbsp;Lizzy Kysela,&nbsp;Colleen Heck,&nbsp;Aaron van Donkelaar,&nbsp;Randall V. Martin,&nbsp;Kevin M. Stewart,&nbsp;Katherine Pruitt","doi":"10.1029/2025GH001585","DOIUrl":"10.1029/2025GH001585","url":null,"abstract":"<p>Since 2000, the American Lung Association (ALA) has published an annual “State of the Air” report, which assigns grades and ranks United States (U.S.) cities and counties based on data from regulatory monitors reported to the Environmental Protection Agency (EPA). We evaluate satellite-derived gridded data sets for fine particulate matter (PM_2.5), as a possible method to support the ALA assessment in counties without regulatory monitors. Our analysis compares two publicly available, annual average, satellite-derived gridded PM_2.5 data sets, allocated to U.S. counties using three different methods. Assigning the 90th percentile gridded value of PM_2.5 within a county as the county-level indicator yields moderately strong agreement between ground-based monitor PM_2.5 results and satellite-derived PM_2.5 results, with a spatial correlation coefficient of 0.76 for 8 years of Washington University global (WashU GL) data. This agreement is evaluated with respect to concentration values, rankings, and the definition of counties as “passing” or “failing” the ALA annual PM_2.5 benchmark of 9.0 μg/m³ (the 2024 EPA National Ambient Air Quality Standard for annual PM_2.5). While most unmonitored counties are “passing” the ALA benchmark, we identify 63 counties that would be classified as “failing” if satellite-based data were used to assign ALA grades. Improving methods to analyze satellite-derived data for comparison with monitor-based metrics can support broader utilization of space-based data in the U.S. and globally.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 7","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13339721/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148406548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Resolution Modeling of Wet Bulb Globe Temperature Reveals Substantial Heat Risks Across Crops and Work Shifts Among Agricultural Workers in Southern California","authors":"Sagar P. Parajuli,&nbsp;Trent Biggs,&nbsp;Corrie Monteverde,&nbsp;Haley Ciborowski,&nbsp;Nicolas Lopez Galvez,&nbsp;Penelope J. E. Quintana,&nbsp;Fernando De Sales,&nbsp;Miguel Angel Zavala Perez,&nbsp;Callum Thompson,&nbsp;Charles Jones","doi":"10.1029/2025GH001604","DOIUrl":"10.1029/2025GH001604","url":null,"abstract":"<p>Farmworkers are particularly vulnerable to heat stress, which can escalate into heat-related illnesses such as heat exhaustion or heat stroke, and can also impact productivity loss. Heat exposure varies considerably depending on season, work-shift timing, acclimatization, and workload. We examine the frequency of heat stress exceedance in the Imperial and Coachella Valleys of southern California using wet bulb globe temperature (WBGT) calculated using the outputs from Weather Research and Forecasting (WRF) model for a reference year of 2020. The critical WBGT threshold of 80℉ is exceeded for more than 500 hr in August, with considerable exceedance in all key harvesting months of April, May, and June. The threshold is exceeded most frequently in August, with daytime (nighttime) exceedance of 96.3% (38.0%) in the Imperial and 72.5% (11.9%) in the Coachella Valleys. Occupational WBGT limits are also exceeded in most crop environments for unacclimatized workers, and even for acclimatized workers during date and sugarcane harvests. Adjusting the work schedule to an early morning or late evening shift can reduce workers' productivity loss by up to 40%. Based on our findings, we propose several strategies to mitigate heat risks among farmworkers: (a) adjusting work hours to include cooler morning or evening hours (b) using WBGT instead of air temperature to monitor heat exposure (c) adopting variable rest-break schedules (d) reducing nighttime heat exposure during summer to allow recovery from daytime heat (e) taking extra precaution in high-risk crop zones (f) avoiding nighttime irrigation during summer, and (g) revising thresholds and definitions used to identify heatwaves.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 7","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13334883/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148438589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association Between Geomagnetic Activity and Unsuccessful Out-of-Hospital Cardiac Arrest.","authors":"Jone Vencloviene, Asta Krikscionaitiene, Linas Darginavicius, Deimante Baksevice, Egle Vaitkaitiene, Dinas Vaitkaitis, Paulius Dobozinskas","doi":"10.1029/2025GH001721","DOIUrl":"10.1029/2025GH001721","url":null,"abstract":"<p><p>Out-of-hospital cardiac arrests (OHCAs) represent a significant global health challenge, with a survival rate <10%. Recent research has demonstrated that geomagnetic activity (GMA) can disrupt the circadian rhythm. Therefore, GMA may affect patient outcomes after an OHCA event wherein resuscitation is attempted. This study involved a retrospective analysis of the Emergency Medical Services (EMS) patient call records and clinical data collected from the Kaunas (Lithuania) EMS digital databases from 1 January 2016 to 31 December 2021. Multivariate logistic regression was used to analyze the association between GMA and the risk of absence of return of spontaneous circulation (ROSC) on the scene, adjusting for potential confounders. Among the 1,507 patients evaluated, 66.6% were male and 47.2% were aged <70 years. A shockable rhythm (SHR) was identified in 436 patients (28.9%), while only 19.9% of patients in the unsuccessful resuscitation group had an SHR. In patients without SHR, a lower rate of ROSC was observed during the period from the second and subsequent days of a geomagnetic storm (GS) to 2 days after the end of the GS. During these days and on days with higher GMA, SHR was associated with a higher probability of achieving ROSC. The impact of SHR on the ROSC was statistically non-significant in the days of GS onset. The association between the risk of absence of ROSC at the scene and higher GMA levels or different GS periods was modified by SHR, with a stronger effect modification observed in males and in patients with a presumed cardiac cause.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":"e2025GH001721"},"PeriodicalIF":5.0,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13288371/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148320020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aurora-Associated Geomagnetic Activity and Health: A Review With Focus on Neurological Implications","authors":"Yashendra Sethi,&nbsp;Vidhi Vora,&nbsp;Amogh Verma,&nbsp;Rahul Bhatt,&nbsp;Manjeet Singh Chaudhary,&nbsp;Hitesh Chopra,&nbsp;Nigel H. Greig","doi":"10.1029/2025GH001710","DOIUrl":"10.1029/2025GH001710","url":null,"abstract":"<p>Geomagnetic activity (GMA), particularly during auroras, has emerged as an intriguing area of research due to its potential health impact. Prior studies indicate that fluctuations in geomagnetic fields can affect diverse physiological and psychological outcomes. The aim of this article is to comprehensively review the impact of GMA on neurological health with an emphasis on implications for patients potentially undergoing a neurosurgical procedure or neurologic/psychiatric assessment. A comprehensive literature review was therefore performed, examining peer-reviewed articles sourced from PubMed and Google Scholar. The focus was on evaluating potential correlations between geomagnetic disturbances (GMDs) and a range of health outcomes, particularly in relation to neurosurgical, neurological and neuropsychiatric contexts. Reported associations included: increased seizure frequency in patients with epilepsy, sleep disturbances affecting recovery, and cognitive impairments that may complicate patient consent processes. Additionally, heightened stress and anxiety levels during geomagnetic storms could pose challenges for patient management in surgical settings. This review underlines that such disturbances can potentially result in significant postoperative complications, particularly in the elderly, necessitating enhanced monitoring and tailored care strategies. Understanding the diverse effects of GMA on health is essential for optimizing patient outcomes, particularly in surgical procedures. This review highlights the need for further research to elucidate underlying GMA-triggered molecular mechanisms and establish evidence-based guidelines that consider geomagnetic conditions in neurological/neuropsychiatric evaluations, surgical planning and postoperative care, especially for vulnerable populations. An enhanced awareness among neurosurgeons, psychiatrist, neurologist and healthcare providers is essential to mitigate potential adverse effects of GMA on patient health and optimize recovery.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13284886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148310058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing the Compound Extreme Temperature and PM2.5 Pollution Events: A Multi-Country Analysis","authors":"Deyang Chen,&nbsp;Mustafa Zahid,&nbsp;Minghao Qiu","doi":"10.1029/2025GH001763","DOIUrl":"https://doi.org/10.1029/2025GH001763","url":null,"abstract":"<p>The increasing frequency of climate extreme events and persistent air pollution challenges pose compound environmental risks, yet the spatiotemporal patterns and trends of compound extreme temperature-air pollution events remain poorly understood globally. In this paper, we quantify the temporal trends and spatial distributions of compound extreme temperature-PM_2.5 pollution events across 10,067 monitor locations in 43 countries spanning 2003–2023. We find that compound extreme heat and PM_2.5 pollution (heat + PM_2.5) events decreased in most countries in our sample (35/43), while compound extreme cold and PM_2.5 pollution (cold + PM_2.5) events showed diverse trends across different nations. Despite the increase in global temperature, cold + PM_2.5 events still represent a substantial component of the compound extreme temperature and PM_2.5 pollution events. Sensitivity analyses using alternative thresholds and MERRA-2 PM_2.5 data sets yield generally consistent results. The spatial heterogeneity in the compound events is linked to the diverse temperature-PM_2.5 relationships, for example, we find higher PM_2.5 concentrations during cold conditions in China, India, and Europe, while the USA and Australia show higher PM_2.5 concentrations during hot conditions. Concentrated populations in high-frequency regions further amplify the exposure burden, with India, Pakistan, and China exhibiting disproportionately higher exposure levels relative to the compound events. Given the likely health impacts of these compound events, our findings suggest that future policies should target temperature-dependent emission activities that will amplify pollution under extreme temperature conditions.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001763","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Residential Greenspace and Domestic Gardens, Genetic Predisposition, and Incident Glaucoma: A Prospective Cohort Study","authors":"Xinyu Zhang,&nbsp;Changjing Han,&nbsp;Xiaojing Liu,&nbsp;Ting Lu,&nbsp;Zixuan Zhang,&nbsp;Xinyu Zhu,&nbsp;Yikeng Huang,&nbsp;Chenxin Li,&nbsp;Xun Xu,&nbsp;Yong Sun,&nbsp;Shuzhi Zhao,&nbsp;Zhi Zheng","doi":"10.1029/2025GH001367","DOIUrl":"https://doi.org/10.1029/2025GH001367","url":null,"abstract":"<p>While greenness has been linked to enhanced physiological and psychological health, its association with glaucoma remains unexplored. This study aims to investigate the effect of residential greenspace and domestic gardens on incident glaucoma. 357, 920 participants from the UK Biobank were included. Land use coverage percentages of greenspace and domestic gardens within 300 and 1,000 m buffers of participants' residential locations were estimated using land use databases. Cox regression models were used to estimate the association between greenness exposures and incident glaucoma. Four-way decomposition models were used to explore potential mediators or moderators in the pathway. Gene-environment interaction effects were tested using multi-trait genetic polygenic risk score of glaucoma and Myocilin p.Gln368Ter genotype. During a median (IQR) follow-up of 13.5 (12.8, 14.1) years, 4, 046 glaucoma cases occurred. After full adjustment, the fourth quartile of greenspace was associated with 17.7% (HR = 0.823, 95%CI 0.723–0.937, <i>p</i> = 0.003) and 19% (HR = 0.810, 95%CI 0.708–0.927, <i>p</i> = 0.002) lower risk of incident glaucoma in 300 and 1000 m buffer. Domestic gardens showed a similar trend (4th quartile vs. 1st quartile: 300 m HR = 0.843, 95%CI 0.742–0.957, <i>p</i> = 0.008; 1,000 m HR = 0.827, 95%CI 0.727–0.941, <i>p</i> = 0.004), though restricted cubic spline analysis showed a nonlinear association in 300 m buffer. Greenspace in 300 m buffer was associated with lower cornea-compensated intraocular pressure. No significant mediating or interactive effects were identified for air pollution, recreational screen time, physical activities, or genetic predisposition. Residential greenspace and domestic gardens may be protective against glaucoma. Therefore, greenspace coverage should be incorporated into land use planning policies for public ocular health promotion.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001367","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparative Analysis of Wildland Fire Smoke PM2.5 Exposure Estimates Across California From 2008 to 2018","authors":"Rachel Connolly,&nbsp;Jenny T. Nguyen,&nbsp;Aron Walker,&nbsp;Joseph Wilkins,&nbsp;Yiqun Ma,&nbsp;Rosana Aguilera,&nbsp;Chen Chen,&nbsp;Alexander Gershunov,&nbsp;Joan A. Casey,&nbsp;Minghao Qiu,&nbsp;Danlu Zhang,&nbsp;Yang Liu,&nbsp;Tarik Benmarhnia,&nbsp;Michael Jerrett,&nbsp;Miriam E. Marlier","doi":"10.1029/2025GH001575","DOIUrl":"10.1029/2025GH001575","url":null,"abstract":"<p>The development of smoke fine particulate matter (PM_2.5) exposure surfaces for estimating air pollution trends and associated health effects has advanced considerably. Currently available smoke exposure products rely on various data sources and modeling techniques, as there is no gold standard method for modeling wildfire smoke PM_2.5. This study compares multiple daily smoke PM_2.5 data sets developed using diverse methodologies spanning 2008–2018. Incorporating metrics for short- and long-term exposure, we compare four data sets at the census tract level in California: one using the U.S. Environmental Protection Agency’s chemical transport model (CTM), the Community Multiscale Air Quality Modeling System (CMAQ); two using statistical methods, also referred to as machine learning (ML) techniques; and one combining these approaches to develop an ML-calibrated CTM-based exposure surface. Our analysis highlights differences between the data sets in terms of long-term exposure metrics, with the CTM data set estimating the highest concentrations overall, and considerable differences between estimates produced by the two ML models. An analysis of six case studies of large fires across the state finds that even data sets with similar inputs and methods produced estimates that varied several-fold, with additional differences by region and over time. Our findings have important implications for quantifying smoke PM_2.5 exposures for use in population health impact studies, which rely on exposure estimates to accurately estimate health burden from pollution exposure.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13273639/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148279397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid Supervised-Unsupervised Modeling for Post-Hurricane Private Well Contamination Risk Score Using Empirical Validation and Community-Informed Assessment","authors":"Jilei Lin,&nbsp;Jennifer Zhang,&nbsp;Ellen Wei,&nbsp;Kyndra Shea,&nbsp;Huixia Judy Wang,&nbsp;Tatiyana V. Apanasovich,&nbsp;Jahred M. Liddie,&nbsp;Erika Hernandez,&nbsp;Crystal Norford,&nbsp;Xindi C. Hu","doi":"10.1029/2026GH001858","DOIUrl":"10.1029/2026GH001858","url":null,"abstract":"<p>Hurricane-related flooding can mobilize microbial and chemical contaminants, while limited well testing and uneven disaster response capacity leave many households relying on private wells at elevated risk, particularly during the early recovery phase when contamination risk is acute. To address this challenge, we propose a data-driven framework for quantifying post-hurricane private well contamination risk. The framework produces a numerical risk score by integrating 78 geospatial variables across three modules representing hazard, physical vulnerability, and social capacity. The score is constructed using a hybrid approach that combines supervised and unsupervised learning to generate interpretable indices grounded in theory and calibrated to real-world data. We applied the framework to western North Carolina following Hurricane Helene and evaluated its performance using post-hurricane well testing data from the North Carolina Department of Health and Human Services together with community-informed assessments in two counties. Higher risk scores were significantly associated with increased total coliform contamination (<i>p</i> = 0.006, Wilcoxon rank-sum test), demonstrating the value of the framework for identifying areas with elevated contamination risk. These findings suggest that the framework can help identify areas with elevated contamination risk following extreme weather events, although predictive performance remains moderate and further systematic evaluation is needed. The framework is designed to be transferable and can be adapted to other storms and regions where geospatial and well testing data are available. Overall, this work provides a practical, data-informed tool to support disaster preparedness, prioritize well testing, and protect private well users after extreme weather events.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13273845/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148279480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil Lead Risks Associated With Urbanization Histories in Springfield MA and Hartford CT, USA","authors":"N. Perdrial,&nbsp;S. L. Walser,&nbsp;E. C. Sirkovich,&nbsp;J. B. Richardson,&nbsp;M. Cope","doi":"10.1029/2026GH001854","DOIUrl":"10.1029/2026GH001854","url":null,"abstract":"<p>Due to legacy leaded products, soil Pb is generally higher in older urban centers triggering substantial implications for environmental equity. By integrating a gridded soil Pb analysis of about 150 samples each in two historically industrial cities (Hartford, CT and Springfield, MA) with block-level census data, we tested the hypotheses that (a) high soil Pb areas correlate spatially with older housing, (b) historical processes of discrimination have caused long-lasting environmental injustices with respect to Pb exposure, and (c) multiple social, demographic and geographic factors intersect in determining areas in need of targeted remediation efforts. Our data and geospatial analysis showed higher Pb concentrations in Hartford than Springfield and confirmed the prevalence of elevated (&gt;200 ppm) Pb in soils closer to older homes in both cities. Using a decision tree statistical partition, we show that exposure to elevated soil Pb was most prevalent in communities with children population higher than the city median, who live in multi-family housing. In Springfield, ethnicity was a significant factor in exposure as census blocks populated by non-Hispanic Whites were least likely to contain lead in soils above 200 ppm. Our analysis highlights that historical discriminatory practices, including redlining, have anchored environmental injustices in the studied communities, creating an invisible legacy challenge recorded in the land and carried across decades. The use of decision trees in the context of soil lead contamination provides a new method to help identify vulnerabilities of marginalized populations, providing quantitative tools to advocate for targeted mitigation and remediation.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13267425/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148266622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}