首页|大气中高风险新污染物的筛查进展及展望

大气中高风险新污染物的筛查进展及展望

扫码查看
空气污染是全球关注的重大环境问题.虽然近年来空气污染水平呈下降趋势,但相同质量PM2.5可能具有不同的毒性强度.亟需突破当前仅基于PM2.5浓度的大气污染控制政策,充分考虑气溶胶的关键危害组分.由于大气组成成分和来源极其复杂,识别大气中未知污染物,尤其是高风险有机污染物面临巨大挑战.本文系统性回顾了通过环境分析和毒性评估,或结合生物分析和化学分析手段,从室外空气、室内空气和个体暴露空气样本中筛查高风险新污染物的策略和最新研究成果.面对空气污染所带来的持续挑战,提出需进一步优化筛查方法,呼吁从暴露组角度开展全链条多方位研究,以深化对大气中高风险新污染物的认知,为建立面向人民生命健康的精准环境治理策略,推动新污染物治理和健康中国建设提供数据支撑.
Screening for high-risk emerging contaminants in the atmosphere:Recent advances and new challenges
Air pollution is a major environmental issue of global concern.According to the latest statistics from the 2019 Global Burden of Disease Study,air pollution is the fourth leading cause of premature death and the largest environmental risk factor worldwide.After the implementation of air quality regulations and technological advances,air pollution levels have declined in recent decades.However,the dose-response relationship between the mass concentration of atmospheric particles and adverse effects is nonlinear.Refined pollution control measures that target key high-risk components in the atmosphere,rather than just particulate matter mass concentrations,may become more important for public health.It is very challenging to identify high-risk organic pollutants in the atmosphere because of the extreme complexity of atmospheric particulate matter components.Nontargeted analysis and suspect screening analysis offer analytical approaches for identifying unknown and unregulated organic compounds.Additional tools and strategies are needed to reduce the number of chemicals of interest and focus analytical efforts on chemicals that may pose high risks to humans and the environment.In this paper,we systematically review the methods and recent findings for screening of high-risk air pollutants:(1)Recognize novel air pollutants using advanced analytical techniques and conduct risk-based prioritization;(2)combine biological and chemical analysis tools to identify key risk drivers in complex atmospheric mixtures.This revealed some previously unknown hazardous pollutants in outdoor air,indoor air,and individual exposure samples.To tackle the persistent challenges of air pollution and enhance the understanding of the link between air pollution and human health,screening methods should be improved.This could be achieved through the development of a global platform for integrating and sharing atmospheric pollutant data,strengthening the integration and analysis of toxic compound data,using machine learning for multi-level mining of big data,and creating toxicological models with high-throughput assessment capabilities that closely resemble human tissues.To enhance our understanding of what we breathe affects our health,it is necessary to consider multiple factors comprehensively,such as mixed exposure effects,unknown toxicological targets,interactions between chemical and biological pollutants,and coupling with natural or social environmental exposure.It is also important to investigate human exposure to atmospheric particulate matters with a focus on susceptible populations and critical windows.The use of multiomics technologies,including genomics,transcriptomics,proteomics,metabolomics,and microbiomics,to analyze the complex multilevel interactions of pollutants with humans has created the exciting new field of exposomics in which exposures are directly linked to disease causal pathways.It is necessary to build statistical analysis models,carry out toxicological simulations,and conduct intervention validation and policy evaluation around the key risk factors,so as to form a risk assessment system with strong causal relationship.Such studies are important for identifying air pollutants for priority control and concentrating efforts to carry out follow-up environmental behavior investigations and toxicity testing.

air pollutionemerging contaminantshigh-riskscreeningpriority

乔林、张旖禾、郑明辉、李亚泰、薛源、樊广涛、邓启红

展开 >

郑州大学公共卫生学院,郑州 450001

中国科学院生态环境研究中心,环境化学与生态毒理学国家重点实验室,北京 100085

北京大学环境科学与工程学院,北京 100871

郑州大学土木工程学院,郑州 450001

展开 >

大气 新污染物 高风险 筛查 优先关注

国家自然科学基金国家自然科学基金

2200615341977369

2024

科学通报
中国科学院国家自然科学基金委员会

科学通报

CSTPCD北大核心
影响因子:1.269
ISSN:0023-074X
年,卷(期):2024.69(6)
  • 65