Environmental Challenges最新文献_第5页

Predicting the impact of climate change on desert locust (Schistocerca gregaria) breeding areas using an ensemble model: A case study of the Wabe Shebelle River Basin, Ethiopia 利用集合模型预测气候变化对沙漠蝗繁殖区的影响：以埃塞俄比亚Wabe Shebelle河流域为例

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-11-03 DOI: 10.1016/j.envc.2025.101365

Demissie Tsega Mallie , Solomon Tekalegn Demissie , Solomon Asfaw Beza , Sitotaw Haile Erena , Sintayehu Workeneh Dejene

Desert locusts (Schistocerca gregaria) pose a significant threat to arid and semi-arid regions due to their rapid reproduction, long-distance migration, and potential to devastate environmental resources. Climate change plays a crucial role in shaping desert locust breeding habitats. This study aims to investigate the impact of climate change on desert locust breeding areas in the Wabe Shebelle River Basin, Ethiopia. Using presence and pseudo-absence data along with environmental variables, an ensemble modeling approach in R (version 4.4.1) was employed to assess breeding areas. The ensemble model incorporated the Generalized Linear Model (GLM), Multivariate Adaptive Regression Splines (MARS), Bioclimatic Modeling (BIOCLIM), Maximum Entropy (MAXENT), Random Forest (RF), and Support Vector Machines (SVM). Pearson correlation tests and Variance Inflation Factors (VIF) were applied to mitigate multicollinearity. Model performance is evaluated using 10-fold cross-validation, spatial partitioning, and AUC analysis. The ensemble model demonstrated strong predictive performance, with AUC values exceeding 0.7 for most models. Under a high-emission scenario (SSP5–8.5), breeding areas are projected to expand significantly, reaching 44,072.46 km² by the 2050s and 45,739.60 km² by the 2070 s. Conversely, under a moderate-emission scenario (SSP2–4.5), the breeding area is expected to decrease to 35,865.08 km² by the 2050 s but expand again to 44,913.33 km² by the 2070 s. These findings highlight the critical influence of climate change on desert locust breeding habitats. Therefore, policymakers should implement effective and sustainable locust management strategies that incorporate climate change projections to safeguard agricultural productivity and livelihoods in vulnerable regions.

沙漠蝗（Schistocerca gregaria）繁殖迅速，迁徙距离远，具有破坏环境资源的潜力，对干旱和半干旱地区构成重大威胁。气候变化在塑造沙漠蝗虫的繁殖栖息地方面起着至关重要的作用。本研究旨在探讨气候变化对埃塞俄比亚Wabe Shebelle河流域沙漠蝗繁殖区的影响。利用存在和伪缺失数据以及环境变量，采用R（版本4.4.1）中的集成建模方法对繁殖区域进行评估。该集成模型包括广义线性模型（GLM）、多元自适应样条回归模型（MARS）、生物气候模型（BIOCLIM）、最大熵模型（MAXENT）、随机森林模型（RF）和支持向量机模型（SVM）。采用Pearson相关检验和方差膨胀因子（VIF）来缓解多重共线性。使用10倍交叉验证、空间划分和AUC分析来评估模型性能。集成模型显示出较强的预测性能，大多数模型的AUC值超过0.7。在高排放情景（SSP5-8.5）下，预计养殖面积将显著扩大，到2050年代达到44,072.46平方公里，到2070年代达到45,739.60平方公里。相反，在中等排放情景（SSP2-4.5）下，预计到2050年繁殖面积将减少到35865.08 km²，但到2070年将再次扩大到44913.33 km²。这些发现强调了气候变化对沙漠蝗虫繁殖栖息地的关键影响。因此，决策者应实施有效和可持续的蝗虫管理战略，将气候变化预测纳入其中，以保障脆弱地区的农业生产力和生计。

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引用次数: 0

Seeding social influence: How peer and descriptive norms encourage green façade adoption at home 播种社会影响：同伴和描述性规范如何鼓励国内采用绿色农业

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-10-30 DOI: 10.1016/j.envc.2025.101364

Kazuma Murakami , Ikuho Kochi

Installing solar photovoltaics (PV) that are visible to others is expensive. Therefore, not everyone is motivated by descriptive norms or signal values to engage in this CO₂ reduction behavior. One inexpensive household CO₂ reduction behavior is to grow green curtains, a type of green façade. Growing green curtains requires daily outdoor tasks and is assumed to have more active communication with neighbors than PV. Therefore, the peer effect is more likely to occur, and the diffusion of green curtains based on the peer effect will significantly contribute to social benefits, such as reducing CO₂ emissions and conserving biodiversity. This study reveals information to promote growing green curtains based on their features: visibility, high interactivity with others, and various functions and effects. A randomized controlled trial was conducted with individuals who had not yet grown green curtains. The results showed that presenting information on the implementation rate of green curtains in other regions as a descriptive norm in a dynamic form is effective. Additionally, the effects of information about the healing and pleasure provided by green curtains were clarified. The results also showed that people affected by these effects have a high degree of social interaction with their neighbors. We believe that these findings contribute to the study of descriptive norms, proximity effects, peer effects, and the promotion of visible prosocial behavior.

安装他人可见的太阳能光伏（PV）是昂贵的。因此，并不是每个人都受到描述性规范或信号值的激励而参与这种二氧化碳减排行为。一种廉价的家庭二氧化碳减排行为是种植绿色窗帘，一种绿色外墙。种植绿色窗帘需要日常的户外任务，并且被认为比光伏有更积极的与邻居交流。因此，同伴效应更容易发生，基于同伴效应的绿色窗帘的扩散将显著有助于减少二氧化碳排放和保护生物多样性等社会效益。本研究从绿色窗帘的可见性、互动性强、功能和效果多样等特点揭示了促进绿色窗帘种植的信息。一项随机对照试验对尚未种植绿色窗帘的个体进行了研究。结果表明，以动态形式呈现其他地区绿色窗帘实施情况的描述性规范信息是有效的。此外，绿色窗帘提供的治疗和愉悦信息的效果也得到了澄清。研究结果还表明，受这些影响的人与邻居的社会互动程度很高。我们认为这些发现有助于研究描述性规范、邻近效应、同伴效应和可见亲社会行为的促进。

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引用次数: 0

Mangrove composition, economic valuation, and disturbances in Mactan Island, Cebu, Philippines 菲律宾宿务Mactan岛红树林的组成、经济价值和干扰

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-10-30 DOI: 10.1016/j.envc.2025.101361

Joed Caballero, Joaicah May Andog, Ivan Jed Bacaling, Marie Nicole Barrientos, Arelie Benito, Althea Claire Caballero, Kevin Sugabo, Mary Jean Tadlip, Joshua Noel Mellor, Ed Andree Sumalinog, Francine Rhey Panuncia, Joselle Rubia, Gwyn Steffani Negro, Maximino III Abejo, Arnel Nudalo, Chembelyn Gella Bayon, Lea Colita, Raamah Rosales, Sylvester Tan Cortes

Mangrove forests worldwide face a critical paradox. They are among the most valuable yet most threatened coastal ecosystems. This study examined the species composition, quantified the economic value, and disturbance level of mangroves in Mactan Island, Cebu, Philippines, to inform conservation and management strategies. A mixed-methods approach combining field assessment, structured interviews, community surveys, and key informant consultations was used to analyze mangrove composition, ecosystem valuation, and anthropogenic disturbances. Across six sampling stations, 21 true mangrove species and five associates were identified, including three under threatened conservation categories. These are Pemphis acidula which is classified as endangered and Acrostichum aureum and A. speciosum categorized as threatened under DAO 2017–11 and IUCN 2.3. Using the Total Economic Valuation (TEV) framework, which integrates both use and non-use values, data from 613 resource users were analyzed. The estimated annual TEV of the mangrove ecosystem was US$20.17 million (₱767.62 million), with direct uses (e.g., fisheries, gleaning, wood, tourism, recreation) contributing 63.8 %, indirect uses (e.g., coastal protection, carbon sequestration, nursery grounds) accounting for 6.5 %, and non-use or bequest values contributing 29.7 %. Despite this high economic value, the mangroves exhibited a high disturbance index (0.82), driven by road construction, urban encroachment, aquaculture conversion, and marine debris. This contrast between substantial economic value and severe ecological disturbance highlights the urgency of strengthening mangrove governance. The strong community willingness to pay for conservation offers a clear opportunity to develop payment for ecosystem service (PES) schemes and targeted restoration initiatives. These strategies can align economic incentives with long-term ecological resilience and community-based conservation.

全世界的红树林都面临着一个严重的悖论。它们是最有价值但也最受威胁的沿海生态系统之一。本研究分析了菲律宾宿务Mactan岛红树林的物种组成，量化了红树林的经济价值和干扰程度，为红树林的保护和管理策略提供依据。采用现场评估、结构化访谈、社区调查和关键信息咨询相结合的混合方法，分析了红树林组成、生态系统价值和人为干扰。通过六个采样站，确定了21种真正的红树林物种和5种类似物种，其中3种属于受威胁的保护类别。根据DAO 2017-11和IUCN 2.3，被列为濒危物种的酸天虱和被列为受威胁物种的金顶虱和A. speciosum。利用综合利用价值和非利用价值的总经济价值（TEV）框架，对613个资源使用者的数据进行了分析。红树林生态系统的年生态价值估计为2017万美元（7.7662亿元），其中直接用途（如渔业、采伐、木材、旅游、娱乐）占63.8%，间接用途（如海岸保护、固碳、苗场）占6.5%，非使用或遗产价值占29.7%。尽管红树林具有很高的经济价值，但由于道路建设、城市侵占、水产养殖转换和海洋垃圾的影响，红树林的干扰指数很高（0.82）。巨大的经济价值与严重的生态干扰之间的对比凸显了加强红树林治理的紧迫性。社区支付保护费用的强烈意愿为制定生态系统服务付费（PES）计划和有针对性的恢复计划提供了明确的机会。这些战略可以将经济激励与长期生态恢复力和基于社区的保护结合起来。

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引用次数: 0

Hazards of residual plastic film pollution in Xinjiang cotton fields and strategies for sustainable control: A review 新疆棉田残膜污染危害及可持续治理对策综述

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-10-30 DOI: 10.1016/j.envc.2025.101363

Xianlin Zhou , Jianjun Yang , Fei cao , Qiang Dong , Meizhen Song

Xinjiang, a pivotal cotton-producing region in China, extensively employs plastic film mulching to enhance cotton yield and quality. However, prolonged and widespread use has led to increasingly severe residual plastic film (RPF) pollution, causing significant adverse impacts on soil, water bodies, and ecosystems. This review critically analyzes the current status of RPF pollution in Xinjiang's cotton fields, examines its detrimental effects on cotton growth, development, and yield, and systematically evaluates its multifaceted environmental consequences. Research indicates that RPF alters soil physical and chemical properties, negatively affecting the cotton growth environment and root development, ultimately diminishing fiber quality. Furthermore, RPF contributes to soil degradation, water pollution, and deterioration of the agricultural production environment. Consequently, this paper synthesizes current sustainable RPF prevention and control strategies. Proposed comprehensive measures include: promoting biodegradable film applications, enhancing film quality standards, optimizing application rates and mulching techniques, improving agricultural management practices, advancing efficient RPF recovery technologies and machinery, innovating recycling and utilization systems, establishing robust collection networks and policy frameworks, strengthening legal regulations and enforcement, implementing diverse public education and awareness campaigns, fostering public participation and oversight mechanisms, and undertaking ecological restoration coupled with long-term monitoring. These strategies aim to elevate societal awareness of RPF pollution and provide a scientific foundation and practical guidance for fostering the harmonious coexistence of Xinjiang's cotton industry and ecological environment.

新疆是中国重要的产棉地区，广泛采用地膜覆盖，以提高棉花产量和品质。然而，长期和广泛的使用导致了日益严重的残余塑料薄膜污染，对土壤、水体和生态系统造成了重大的不利影响。本文批判性地分析了新疆棉田RPF污染现状，考察了其对棉花生长、发育和产量的不利影响，并系统地评估了其多方面的环境后果。研究表明，RPF改变了土壤理化性质，对棉花生长环境和根系发育产生负面影响，最终导致棉花纤维品质下降。此外，RPF还会导致土壤退化、水污染和农业生产环境恶化。因此，本文综合了目前可持续的RPF预防和控制策略。建议的综合措施包括：推广生物可降解薄膜的应用，提高薄膜质量标准，优化施用量和覆盖技术，改进农业管理方法，推进高效的生物可降解膜回收技术和机械，创新回收利用系统，建立健全的收集网络和政策框架，加强法律法规和执法，开展各种公众教育和宣传活动，健全公众参与和监督机制，坚持生态修复与长期监测相结合。这些策略旨在提高社会对RPF污染的认识，为促进新疆棉花产业与生态环境的和谐共处提供科学依据和实践指导。

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引用次数: 0

Association between wildfire smoke exposure and parents’ adoption of protective behaviours: Exploring the role of objective and subjective smoke exposure 野火烟雾暴露与父母采取保护行为之间的关系：探讨客观和主观烟雾暴露的作用

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-10-30 DOI: 10.1016/j.envc.2025.101362

Catherine E. Slavik , Daniel A. Chapman , Stephanie E. Cleland , Perry Hystad , Ellen Peters

Exposure to wildfire smoke poses a significant threat, particularly to children, even at low concentrations. Although several agencies monitor and disseminate air quality data, some parents rely on sensory cues to decide on protective behaviours, such as using air purifiers. We investigated relationships between objective smoke exposure measures (from air monitoring data), parents’ subjective perceptions of smoke exposure (perceived through sight or smell), and their protective behaviours during wildfire smoke events. We combined survey responses from 2086 parents in wildfire-prone regions of the western US and Canada with three and a half years of wildfire smoke data (2020–2023). Parents’ subjective perceptions of being exposed to smoke were associated with objective smoke exposure measures; however, subjective exposure was more strongly related to protective behaviours than objective exposure measures. Specifically, parents who perceived being exposed to wildfire smoke took, on average, more than one additional protective action (b = 1.11, 95% CI: 0.92‒1.30), compared to those not who did not report smoke exposure. In comparison, every 10 µg/m³ increase of PM2.5 on smoke days predicted only a 0.23 increase in the number of protective actions adopted (95% CI: 0.06‒0.40). Exploratory analyses indicated non-linear relationships between objective smoke exposure and protective behaviours, with initial increases prompting more actions, plateauing at moderate levels, and rising again at higher exposure levels. As wildfire smoke can be harmful even when not visible or detectable by smell, smoke messaging should better connect objective air quality data like the Air Quality Index with parents’ subjective perceptions of wildfire smoke.

暴露在野火烟雾中，即使浓度很低，也会造成重大威胁，特别是对儿童。虽然有几个机构监测和传播空气质量数据，但一些父母依靠感官线索来决定保护行为，比如使用空气净化器。我们调查了客观烟雾暴露措施（来自空气监测数据）、父母对烟雾暴露的主观感知（通过视觉或嗅觉感知）以及他们在野火烟雾事件中的保护行为之间的关系。我们将来自美国西部和加拿大易发野火地区2086名家长的调查反馈与三年半的野火烟雾数据（2020-2023）相结合。父母对吸烟暴露的主观认知与客观吸烟暴露测量相关；然而，与客观暴露措施相比，主观暴露与保护行为的关系更为密切。具体而言，与没有报告烟雾暴露的父母相比，感知到暴露于野火烟雾的父母平均采取了不止一项额外的保护措施（b = 1.11, 95% CI: 0.92-1.30）。相比之下，在烟雾日，PM2.5每增加10微克/立方米，所采取的保护措施数量仅增加0.23 （95% CI: 0.06-0.40）。探索性分析表明，客观烟雾暴露与保护行为之间存在非线性关系，最初的增加会促使更多的行动，在中等水平时达到稳定，在较高的暴露水平时再次上升。由于野火烟雾即使在看不见或闻不到的情况下也可能有害，因此烟雾信息应该更好地将空气质量指数（air quality Index）等客观空气质量数据与家长对野火烟雾的主观感知联系起来。

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引用次数: 0

Modeling wildfires in the Alpine context: Lessons learnt from real case studies 在高山环境中模拟野火：从真实案例研究中吸取的教训

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-10-29 DOI: 10.1016/j.envc.2025.101357

Luca Malanchini , Nicolò Perello , Andrea Trucchia , Lorenzo M.W. Rossi , Paolo Fiorucci , Giorgio Vacchiano

In the Alpine region, climate change is altering the predisposing factors of wildfires, leading to an increase in their frequency and intensity. This trend, combined with the inherent vulnerability of Alpine forest stands, underscores the growing importance of fire modeling as a fundamental tool to support both prevention strategies and emergency response. This study compares two wildfire simulation models — FlamMap and PROPAGATOR — which, although both widely used in Italy, are based on fundamentally different modeling approaches.

The models are applied to three significant case studies in Lombardia’s Alpine area that took place in the period 2017–2022 (Tirano, Campolaro, and Sonico Wildfires), allowing a comparison of their performance in reproducing fire spread, rate of spread, and fireline intensity under varying topographic, vegetational, and meteorological conditions. Results indicate that both models reasonably captured the propagation of the three wildfires, although substantial differences emerged in fireline intensity and rate of spread, reflecting their distinct modeling assumptions. A closer examination of the outputs, combined with the specific input data required by each model, suggests that FlamMap is more suitable for planning contexts due to its ability to capture fine-scale fuel-topography interactions, while PROPAGATOR is better suited for operational scenarios thanks to its flexibility, fast implementation and computation, and capacity to incorporate time-varying wind.

The analysis benefited from detailed information provided by local managers directly involved in the events, which helped reconstruct the actual fire dynamics and evaluate model outputs against real-world cases. These findings emphasize the critical role of accurate wind and fuel data, as well as the need for a structured database of past wildfires in the Alpine context to improve model calibration and reliability. Overall, this study provides practical insights to support stakeholders in selecting appropriate modeling tools across different phases of wildfire risk management and underscores the need for further refinement of simulation systems tailored to complex mountain landscapes.

在高寒地区，气候变化正在改变野火的易发因素，导致其发生频率和强度增加。这一趋势，再加上高山林分固有的脆弱性，凸显了火灾建模作为支持预防战略和应急反应的基本工具日益重要。本研究比较了两种野火模拟模型——FlamMap和PROPAGATOR——尽管这两种模型在意大利广泛使用，但它们基于根本不同的建模方法。这些模型应用于伦巴第高山地区2017-2022年期间的三个重要案例研究（提拉诺、坎波拉罗和索尼科野火），比较了它们在不同地形、植被和气象条件下再现火灾蔓延、蔓延速度和火线强度的表现。结果表明，两个模型都合理地反映了三种野火的传播，尽管在火线强度和蔓延速度上存在实质性差异，反映了它们不同的建模假设。对输出进行更仔细的检查，结合每个模型所需的具体输入数据，表明FlamMap更适合规划环境，因为它能够捕获精细尺度的燃料-地形相互作用，而PROPAGATOR由于其灵活性、快速实现和计算以及纳入时变风的能力而更适合操作场景。该分析得益于直接参与事件的当地管理人员提供的详细信息，这些信息有助于重建实际的火灾动态，并根据真实案例评估模型输出。这些发现强调了准确的风和燃料数据的关键作用，以及对高山地区过去野火的结构化数据库的需求，以提高模型校准和可靠性。总体而言，本研究为利益相关者在野火风险管理的不同阶段选择合适的建模工具提供了实用的见解，并强调了进一步完善针对复杂山地景观的模拟系统的必要性。

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引用次数: 0

Understanding housing flood resilience through Bayesian networks: A data-driven framework 通过贝叶斯网络了解住房抗洪能力：一个数据驱动的框架

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-10-28 DOI: 10.1016/j.envc.2025.101358

Pavithra Rathnasiri, Onaopepo Adeniyi, Niraj Thurairajah

Flooding poses a significant threat to housing facilities, particularly in flood-prone areas. To mitigate ongoing flood damage, it is crucial to enhance the understanding of underlying factors and the dynamic interactions among elements that contribute to such damage. This study introduces a data-driven Bayesian network model to enhance housing flood resilience, with a particular focus on the interactions between flood-related components. The resilience was focused on the key parameters of rapidity, redundancy, robustness, and resourcefulness, and these parameters were assessed to evaluate their impact on overall housing flood resilience. By considering the intricate interrelationships between floodwaters, terrain and housing, data variables relevant to flood resilience were first collected from three UK regions: Manchester, Cumbria, and York, across 18 zones categorised by high, medium, and low flood risk levels. Principal Component Analysis was employed to identify the most influential variables at each risk level, followed by Pearson correlation to determine their significant interrelationships and dependencies. In total, nine separate Bayesian network models were developed for each risk level using GeNIe software. The models quantified resilience levels, offering a flexible and robust tool for real-time flood resilience assessment. The results revealed distinct patterns of resilience across different risk levels, highlighting the importance of geographic and risk-specific strategies for enhancing flood resilience in housing. This study offers a transferable methodology and adaptable models, which is a significant contribution to the knowledge base for improving flood resilience globally, and it sets a new standard for data integration in resilience assessment.

洪水对住房设施构成重大威胁，特别是在易受洪水影响的地区。为了减轻持续的洪水破坏，加强对潜在因素和造成这种破坏的要素之间动态相互作用的理解是至关重要的。本研究引入了一个数据驱动的贝叶斯网络模型来增强住房的抗洪能力，特别关注洪水相关成分之间的相互作用。弹性主要集中在快速性、冗余性、鲁棒性和资源性等关键参数上，并对这些参数进行了评估，以评估它们对整体住房抗洪能力的影响。通过考虑洪水、地形和住房之间错综复杂的相互关系，首先从英国三个地区收集了与洪水恢复力相关的数据变量：曼彻斯特、坎布里亚郡和约克郡，这些地区分为高、中、低洪水风险水平的18个区域。采用主成分分析来确定每个风险水平上最具影响力的变量，然后采用Pearson相关性来确定其显著的相互关系和依赖关系。总共使用GeNIe软件为每个风险级别开发了9个独立的贝叶斯网络模型。该模型量化了恢复能力水平，为实时洪水恢复能力评估提供了一个灵活而强大的工具。研究结果揭示了不同风险水平的抗洪能力的不同模式，强调了提高住房抗洪能力的地理和风险特定策略的重要性。该研究提供了一种可转移的方法和可适应的模型，为提高全球洪水恢复力提供了重要的知识库，并为恢复力评估的数据整合设定了新的标准。

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引用次数: 0

Interannual variations in PM10 and PM2.5 due to wildfires in four air quality monitoring networks in the Colombian caribbean 哥伦比亚加勒比地区四个空气质量监测网络中野火引起的PM10和PM2.5的年际变化

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-10-27 DOI: 10.1016/j.envc.2025.101360

Roberto E. Rojano , Heli A. Arregoces , Gloria Restrepo

Particulate matter (PM₁₀ and PM_2.5) significantly impacts air quality and public health, particularly in regions with meteorological and topographical characteristics prone to wildfires. In the Colombian Caribbean, wildfires and urban emissions worsen particulate matter pollution. However, studies examining interannual trends and the specific contributions of wildfires to air quality are limited. This study examines the interannual variations in PM₁₀ and PM_2.5 concentrations across four cities in the Colombian Caribbean between 2018 and 2024, using data from Colombia's Air Quality Information System. The determination of particulate matter was analyzed using gravimetric and optical techniques. Satellite data were employed to assess wildfire activity and its influence on regional air quality. The highest number of wildfires in the Colombian Caribbean usually occurs during January, February, and March, which is characterized as the primary dry period in the region, extending from December to March. The PM₁₀ and PM_2.5 concentrations ranged between 17.36 - 48.16 µg/m³ and 9.55 - 19.94 µg/m³, respectively. The results showed that wildfires significantly elevated PM_2.5 levels, in addition to the contribution of emissions from local activities. Cluster analysis, potential source contribution function (PSCF), and potential impact (PI) analyses reveal that air mass transport predominantly originating from the northeast, influenced by wildfires, directly impacts high PM₁₀ concentrations at the Caribbean air quality monitoring sites. This research reveals that wildfire, combined with local emissions, deteriorates air quality, highlighting the importance of implementing strategies to protect vulnerable populations.

颗粒物（PM10和PM2.5）严重影响空气质量和公众健康，特别是在具有易发生野火的气象和地形特征的地区。在哥伦比亚加勒比海地区，野火和城市排放加剧了颗粒物污染。然而，研究年际趋势和野火对空气质量的具体贡献的研究有限。本研究使用哥伦比亚空气质量信息系统的数据，研究了2018年至2024年间哥伦比亚加勒比地区四个城市PM10和PM2.5浓度的年际变化。用重量法和光学技术分析了颗粒物的测定方法。利用卫星数据评估野火活动及其对区域空气质量的影响。哥伦比亚加勒比地区的野火数量最多，通常发生在1月、2月和3月，这是该地区的主要干旱期，从12月持续到3月。PM10和PM2.5浓度分别在17.36 ~ 48.16µg/m³和9.55 ~ 19.94µg/m³之间。结果表明，除了当地活动的排放外，野火还显著提高了PM2.5水平。聚类分析、潜在源贡献函数（PSCF）和潜在影响（PI）分析表明，受野火影响，主要源自东北的气团运输直接影响加勒比海地区空气质量监测点的高PM10浓度。这项研究表明，野火与当地排放相结合，使空气质量恶化，突出了实施保护弱势群体战略的重要性。

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引用次数: 0

Mapping risk: Spatial analysis of 2,4-D herbicide emissions and colorectal cancer 测绘风险：2,4- d除草剂排放与结直肠癌的空间分析

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-10-27 DOI: 10.1016/j.envc.2025.101356

Danny Baxter , Dan A. Dixon , Andrew J. Morris , Tongzhang Zheng , Yong Zhu

Colorectal cancer remains a major public health concern in Arkansas and across the United States, disproportionately affecting rural and vulnerable populations. Beyond established lifestyle and genetic factors, environmental exposures, particularly agricultural chemicals, are increasingly recognized as potential contributors. In this ecological study, we screened 133 county-level estimated air pollutants to identify candidates associated with colorectal cancer incidence rates, focusing on Arkansas due to its agricultural economy and widespread herbicide use. Using publicly available environmental and cancer registry data, we applied spatial mapping, correlation tests, linear regression, and spatial regression models. Among screened pollutants, 2,4-Dichlorophenoxyacetic acid (2,4-D), a widely used herbicide, emerged as the top candidate. In Arkansas, 2,4-D emissions showed a strong positive association with colorectal cancer incidence rates (Spearman ρ = 0.338, p = 0.003; linear regression β1 = 6.28, p = 0.001), with high-emission counties aligning spatially with elevated incidence. This relationship was further confirmed in analyses of more than 2,500 U.S. counties, where 2,4-D emissions remained significantly associated with colorectal cancer (linear regression β1 = 5.94, p < 0.001; spatial regression β1 = 2.55, p = 0.001). Spatial regression improved model fit and accounted for geographic autocorrelation in both datasets. These findings suggest a potential association between 2,4-D emissions and colorectal cancer incidence rates, particularly in agricultural regions such as Arkansas. While causal inference is limited by the ecological design, the consistency of results warrants follow-up with individual-level, longitudinal, and mechanistic studies.

结直肠癌仍然是阿肯色州和整个美国的一个主要公共卫生问题，对农村和弱势群体的影响尤为严重。除了既定的生活方式和遗传因素外，环境暴露，特别是农用化学品，也日益被认为是潜在的因素。在这项生态研究中，我们筛选了133个县级估计的空气污染物，以确定与结直肠癌发病率相关的候选污染物，由于其农业经济和广泛使用除草剂，我们将重点放在阿肯色州。利用可公开获得的环境和癌症登记数据，我们应用了空间制图、相关检验、线性回归和空间回归模型。在筛选的污染物中，2,4-二氯苯氧乙酸（2,4- d）是一种广泛使用的除草剂。在阿肯色州，2,4- d排放与结直肠癌发病率呈强正相关（Spearman ρ = 0.338, p = 0.003；线性回归β1 = 6.28, p = 0.001），高排放县与高发病率在空间上一致。这一关系在美国2500多个县的分析中得到进一步证实，在这些县，2,4- d排放与结直肠癌仍然显著相关（线性回归β1 = 5.94, p < 0.001；空间回归β1 = 2.55, p = 0.001）。空间回归改善了模型拟合，并考虑了两个数据集的地理自相关。这些发现表明，2,4- d排放与结直肠癌发病率之间存在潜在关联，尤其是在阿肯色州等农业地区。虽然因果推理受到生态设计的限制，但结果的一致性保证了个人水平、纵向和机制研究的后续研究。

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引用次数: 0

What drives the regeneration dynamics in Central Himalayan Mountain Forests of Nepal? 是什么推动了尼泊尔喜马拉雅山脉中部森林的更新动态？

Q2 Environmental Science

Environmental Challenges

Pub Date : 2025-10-26 DOI: 10.1016/j.envc.2025.101359

Santosh Ayer , Bimal Kumar Yadav , Kishor Prasad Bhatta

Although forest regeneration has been studied in Nepal’s mountain regions, most research has emphasized single factors such as elevation or canopy cover, with few studies evaluating multiple drivers together. Stage-wise transitions and associated shifts in composition and diversity also remain understudied, particularly in protected areas under passive management. Regeneration dynamics in the Sikles region of the Annapurna Conservation Area were modelled using linear, quadratic, and generalized additive models (GAMs). Principal component analysis (PCA) simplified five soil variables into two composite gradients. Single predictor GAMs examined independent effects of topography, stand structure, and soils, while multivariate GAMs tested their combined influence. Results showed a clear shift in composition and reduced richness from seedlings to saplings, indicating demographic constraints, though evidence for bottlenecks was mixed. Cold-adapted taxa such as Rhododendron spp. dominated saplings at higher elevations. Seedling density was highest at 1500–2000 m (mean = 10,250 ha⁻¹), while sapling density peaked at 3500–4000 m (median = 6000 ha⁻¹). Diversity indices followed unimodal trends with elevation, with the strongest single predictor GAM fit for seedling richness (adj. R² = 0.41; p < 0.001). Single-predictor GAMs highlighted stage-specific drivers: seedling density was strongly elevation dependent, while sapling density declined with canopy cover and tree density, and soil fertility (PC2) promoted seedling establishment at lower elevations. Multivariate GAMs revealed stronger combined effects, with seedling density shaped jointly by elevation and soil fertility (adj. R² = 0.62) and sapling density constrained by canopy structure and soil fertility (adj. R² = 0.58). These findings show that while single-predictor models identify individual signals, multivariate approaches capture interacting drivers. Conservation strategies should therefore integrate soil management at lower elevations, canopy moderation at mid- to high elevations, and stage-specific monitoring to sustain regeneration under climate change.

尽管在尼泊尔山区研究了森林再生，但大多数研究都强调了海拔或冠层覆盖等单一因素，很少有研究同时评估多个驱动因素。分阶段过渡和相关的组成和多样性变化也仍未得到充分研究，特别是在被动管理的保护区。采用线性模型、二次模型和广义加性模型（GAMs）对安纳普尔纳森林保护区Sikles地区的更新动态进行了模拟。主成分分析（PCA）将5个土壤变量简化为2个复合梯度。单一预测因子GAMs检测地形、林分结构和土壤的独立影响，而多元GAMs检测它们的综合影响。结果显示，植物的组成发生了明显的变化，从幼苗到树苗的丰富度减少，表明存在人口限制，尽管存在瓶颈的证据好坏参半。在高海拔地区，树苗以杜鹃花等冷适应类群为主。苗木密度在1500-2000米处最高（平均= 10250公顷⁻¹），而树苗密度在3500-4000米处最高（中位数= 6000公顷⁻¹）。多样性指数随海拔高度呈单峰趋势，单一预测因子GAM最适合幼苗丰富度（相对值R²= 0.41;p < 0.001）。单预测因子GAMs强调了苗期特异性驱动因素：幼苗密度高度依赖，而幼苗密度随冠层盖度和乔木密度而下降，土壤肥力（PC2）促进了低海拔地区的幼苗形成。多变量GAMs显示出较强的联合效应，幼苗密度受海拔和土壤肥力的共同影响（adj. R²= 0.62），树冠结构和土壤肥力对树苗密度的影响（adj. R²= 0.58）。这些发现表明，当单一预测模型识别单个信号时，多元方法捕获相互作用的驱动因素。因此，保护策略应综合考虑低海拔地区的土壤管理、中高海拔地区的冠层调节和特定阶段的监测，以维持气候变化下的更新。

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引用次数: 0