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| 1 | Characteristics of PM_(2.5) pollution in Beijing after the improvement of air quality显示文摘Following the implementation of the strictest clean air policies to date in Beijing,the physicochemical characteristics and sources of PM_(2.5) have changed over the past few years.To improve pollution reduction policies and subsequent air quality further,it is necessary to explore the changes in PM_(2.5) over time.In this study,over one year(2017-2018)field study based on filter sampling(TH-150C;Wuhan Tianhong,China)was conducted in Fengtai District,Beijing,revealed that the annual average PM_(2.5) concentration(64.8±43.1μg/m^3)was significantly lower than in previous years and the highest PM_(2.5) concentration occurred in spring(84.4±59.9μg/m^3).Secondary nitrate was the largest source and accounted for 25.7%of the measured PM_(2.5).Vehicular emission,the second largest source(17.6%),deserves more attention when considering the increase in the number of motor vehicles and its contribution to gaseous pollutants.In addition,the contribution from coal combustion to PM_(2.5) decreased significantly.During weekends,the contribution from EC and NO3−increased whereas the contributions from SO4^2−,OM,and trace elements decreased,compared with weekdays.During the period of residential heating,PM_(2.5) mass decreased by 23.1%,compared with non-heating period,while the contributions from coal combustion and vehicular emission,and related species increased.With the aggravation of pollution,the contribution of vehicular emission and secondary sulfate increased and then decreased,while the contribution of NO3−and secondary nitrate continued to increase,and accounted for 34.0%and 57.5%of the PM_(2.5) during the heavily polluted days,respectively. | Xiaojuan Huang Guiqian Tang Junke Zhang Baoxian Liu Chao Liu Jin Zhang Leilei Cong Mengtian Cheng Guangxuan Yan Wenkang Gao Yinghong Wang Yuesi Wang | 2021 | Journal of Environmental Sciences2021，33，2： | 14 |
| 2 | 京津冀典型城市冬季人为源减排与气象条件对PM_(2.5)污染影响显示文摘本研究基于采样分析与WRF-CAMx-PSAT模式分析了2018年1月北京和唐山PM_(2.5)的组分特征、传输特征和来源解析.结果表明,2018年1月北京和唐山水溶性无机离子占PM_(2.5)质量浓度的49.59%和39.13%,两地NO^(-)_(3)/SO^(2-)_(4)分别为2.02和1.51,均受移动源主导,北京和唐山PM_(2.5)外来贡献分别占总浓度的48.74%和30.67%,除此之外主要受到邻近局地、西北通道和西南通道这3个方面的污染输送.在污染日时段,两地受西南通道污染贡献分别上升9.65%和15.02%.北京PM_(2.5)污染浓度贡献最大的是移动源和扬尘源,二次离子受区域输入影响较为明显,唐山则以移动源和工业源为主,且一次颗粒物和SO^(2-)_(4)的本地贡献十分显著.与2013年相比,水溶性离子主导组分由SO^(2-)_(4)向NO^(-)_(3)转变,主要污染源由燃煤源和工业源向移动源和扬尘源转变,同时2018年气象条件对于污染的缓解也比2013年更为有利,其中二次离子的气象影响变化与这两年的相对湿度变化差异紧密相关. | 邵玄逸 王晓琦 钟嶷盛 王瑞鹏 | 2021 | 环境科学2021，42，9： | 13 |
| 3 | 2013—2017年珠江三角洲主要大气污染控制措施减排效果评估显示文摘自2013年《大气污染防治行动计划》发布以来,珠江三角洲(PRD)地区实施了严格的大气污染防控政策,在全国率先实现PM_(2.5)浓度连续3年达标,然而,已实施的控制措施对污染物的减排效果尚不清楚.因此,本研究通过广泛收集2013—2017年珠三角地区大气污染源活动水平数据与控制措施,建立2013—2017年实际控制与未控制情景的污染物趋势排放清单,对主要控制措施的减排效果进行了量化.结果表明,2013—2017年珠三角地区SO_(2)、NO_(x)、PM_(10)、PM_(2.5)和VOCs 5种污染物排放分别下降了55%、24%、55%、54%和10%.相比于未控制情景,实际控制情景下2017年5种污染物分别实现61%、40%、68%、70%和41%的减排.在各类管控措施中,工业提标对5种污染物减排分别贡献了39%、46%、66%、69%和25%;销号整治对VOCs减排贡献最大(32%),对其它污染物减排贡献约10%;清洁能源改造主要对SO_(2)和PM减排有所贡献,其中,煤改气、低硫煤、低硫油对SO_(2)减排有主要贡献(均为15%左右),低灰分煤对PM_(10)(12%)和PM_(2.5)(19%)减排有较大贡献;机动车提标、淘汰黄标车对NO_(x)(22%、17%)和VOCs(23%、12%)减排有较大贡献.本研究可为珠三角和其它地区针对不同大气污染物科学制定防控政策与措施提供基础数据和科学支撑. | 崔晓珍 沙青娥 李成 王毓铮 吴莉莉 张雪驰 郑君瑜 颜敏 | 2021 | 环境科学学报2021，41，5： | 11 |
| 4 | Impact of clean air action on PM2.5 pollution in China显示文摘China suffers from severe air pollution in the past decades,characterized by high-levels of fine particulate matter(PM2.5)concentrations.To mitigate PM2.5 pollution,the Chinese government issued the Air Pollution Prevention and Control Action Plan(referred to as the Clean Air Action hereinafter)in 2013,which requires the three key regions,ie..,Beijing-Tianjin-Hebei(BTH),the Yangtze River Delta(YRD)and the Pearl River Delta(PRD),to reduce PM2.5 concentrations by 15-25%from 2013-2017,and all other cities to reduce PM10 concentrations by 10%compared to 2012(State Council of the People's Republic of China,2013). | Qiang ZHANG Guannan GENG | 2019 | Science China Earth Sciences2019，62，12： | 6 |
| 5 | 北京地区2019年2~3月供暖结束前后两次污染过程特征分析显示文摘以2019年2~3月北京两次污染过程为例,针对气象要素及污染物浓度进行特征分析,利用后向轨迹及WRF-CAMx模式,分析供暖结束前后的污染物演变规律,并探讨气象条件、区域输送及二次转化等对污染过程的影响.结果表明,2月21~24日(过程1)和3月18~20日(过程2)平均ρ(PM_(2.5))差异不大,分别为100.1μg·m^(-3)和97.2μg·m^(-3),但过程1平均峰值偏高、日变化明显、过程发展迅速和有两个峰值阶段,且为区域性污染,而过程2更倾向于北京局地污染.两次过程逐时ρ(SO_(2))均不超16μg·m^(-3),供暖燃煤治理效果显著,但过程1的SO_(2)存在夜间次峰值,体现供暖排放影响.过程1的ρ(CO)较高,尤其是2月21~22日前后ρ(CO)/ρ(SO_(2))升高,且区域中南部城市及北京南部背景站污染高于城区,表明过程1扩散条件不利,且第一个峰值主要受区域输送影响.过程2的ρ(PM_(2.5))/ρ(CO)偏高,表明二次生成PM_(2.5)占比略大;ρ(NO_(2))/ρ(CO)、ρ(SO_(2))/ρ(CO)和ρ(SO_(4)^(2-))/ρ(PM_(2.5))偏大,SOR与过程1持平,表明过程1更有利于气体相态转化,过程2受工业燃煤影响更大.但将过程1分阶段分析显示,过程1第二阶段与过程2的PM_(2.5)二次生成指征相似,均高于过程1第一阶段,即过程1第二个峰值与过程2主要与本地排放和化学转化相关.WRF-CMAx对污染物演变趋势有较好的再现能力.同化试验对PM_(2.5)趋势模拟显著提升,提高了与观测的相关性,但模拟值偏低;对NO_(2)的模拟2月偏低、3月偏高,对SO_(2)模拟明显偏高有一定纠正;此外,过程2中北京污染物浓度对河北的敏感性相对过程1偏低,即过程1受区域输送影响更大.模式对污染暴发性增长的模拟亟待提升,污染物种类对减排的响应及大气氧化剂和气溶胶性质相关的反馈等可能是影响模拟效果的重要原因,需进一步研究. | 尹晓梅 蒲维维 王继康 刘湘雪 乔林 | 2021 | 环境科学2021，42，5： | 6 |
| 6 | 2017—2019年中天山北坡城市群大气污染及污染天气类型特征显示文摘利用2017—2019年中天山北坡城市群(乌鲁木齐市、昌吉市、石河子市、五家渠市)逐时大气污染物监测数据及气象数据,分析了大气污染物年内变化和污染天气类型特征。结果表明:(1)中天山北坡4座城市6类大气污染物中PM_(2.5)超标日数最多(年均94~104 d),年均浓度介于64~73μg·m^(-3),且五家渠市>乌鲁木齐市>石河子市>昌吉市。采暖期PM_(2.5)浓度在100~118μg·m^(-3)之间,是非采暖期的4.00~5.00倍,靠近山前地带的城市PM_(2.5)浓度日变化大体呈现“双峰双谷型”。(2)4座城市污染天气类型主要分为静稳型、沙尘型和特殊型,其中静稳型占86.2%~93.6%、沙尘型占5.8%~13.2%。静稳型污染天气多出现在冬季,沙尘型主要出现在春、秋季节。静稳型污染天气中Ⅴ-Ⅵ级污染级别占比45.8%~56.6%,沙尘型污染天气中Ⅴ-Ⅵ级污染级别占比14.9%~29.4%。(3)静稳型和沙尘型污染天气下PM_(2.5)和PM_(10)浓度都存在显著的线性相关,前者PM_(10)浓度是PM_(2.5)的1.26倍,而后者达3.16倍,此倍数可以作为区分静稳型和沙尘型污染天气的判据。 | 李淑婷 李霞 毛列尼·阿依提看 钟玉婷 王慧琴 | 2022 | 干旱区地理2022，45，4： | 5 |
| 7 | 选择性催化氧化含氨废气为氮气的研究进展显示文摘氨气作为一种有毒有害气体,排放到大气中会对人体健康和生态环境产生重要的危害.选择性催化氧化技术是一种高效且有潜力的氨气处理技术,将NH3直接转化为N2和H2O,是当前大气污染控制领域研究的热点,受到人们越来越多的关注.本文重点介绍了Ag基催化剂、Cu基催化剂在氨氧化反应中的研究进展.首先综述了载体效应、元素/氧化物掺杂、气氛预处理对Ag基催化剂的影响,负载型和复合型Cu基催化剂以及整体型催化剂的催化性能及其影响因素.然后阐述了催化剂上催化氧化NH3的反应机理,包括NH-HNO机理、N2H4机理以及iSCR机理,介绍了基于iSCR机理设计的双功能催化剂的研究进展.最后对Ag基和Cu基催化剂的研究方向和发展趋势进行了展望. | 孙洪春 曲振平 | 2020 | 科学通报2020，65，26： | 5 |
| 8 | PM_(2.5)and water-soluble inorganic ion concentrations decreased faster in urban than rural areas in China显示文摘We investigated variations of PM_(2.5)and water-soluble inorganic ions chemical characteristics at nine urban and rural sites in China using ground-based observations.From 2015 to 2019,mean PM_(2.5)concentration across all sites decreased by 41.9μg/m~3with a decline of 46%at urban sites and 28%at rural sites,where secondary inorganic aerosol(SIAs)contributed to 21%(urban sites)and 17%(rural sites)of the decreased PM_(2.5).SIAs concentrations underwent a decline at urban locations,while sulfate(SO_(4)^(2–)),nitrate(NO_(3)^(–)),and ammonium(NH_(4)^(+))decreased by 49.5%,31.3%and 31.6%,respectively.However,only SO_(4)^(2–)decreased at rural sites,NO_(3)^(–)increased by 21%and NH_(4)^(+)decreased slightly.Those changes contributed to an overall SIAs increase in 2019.Higher molar ratios of NO_(3)^(–)to SO_(4)^(2–)and NH_(4)^(+)to SO_(4)^(2–)were observed at urban sites than rural sites,being highest in the heavily polluted days.Mean molar ratios of NH_(3)/NH_xwere higher in 2019 than 2015 at both urban and rural sites,implying increasing NH_xremained as free NH_(3).Our observations indicated a slower transition from sulfate-driven to nitrate-driven aerosol pollution and less efficient control of NO_(x)than SO_(2)related aerosol formation in rural regions than urban regions.Moreover,the common factor at urban and rural sites appears to be a combination of lower SO_(4)^(2–)levels and an increasing fraction of NO_(3)^(–)to PM_(2.5)under NH_(4)^(+)-rich conditions.Our findings imply that synchronous reduction in NO_(x)and NH_(3)emissions especially rural areas would be effective to mitigate NO_(3)^(–)-driven aerosol pollution. | Yangyang Zhang Aohan Tang Chen Wang Xin Ma Yunzhe Li Wen Xu Xiaoping Xia Aihua Zheng Wenqing Li Zengguo Fang Xiufen Zhao Xianlong Peng Yuping Zhang Jian Han Lijuan Zhang Jeffrey L.Collett Jr Xuejun Liu | 2022 | Journal of Environmental Sciences2022，34，12： | 2 |
| 9 | 大气污染物监测数据异常值判别方法研究显示文摘大气环境监测数据的质控,特别是异常数据的精准判别是准确分析大气污染成因的重要前提.目前对于异常值的判别主要基于人工经验,这对于快速有效地从海量环境数据中剔除异常值进而保证分析数据的准确性带来巨大挑战.结合大气污染物监测数据的时间序列波动特点,本文基于滑动窗口机制和统计学指标分别构建了滑动四分位、滑动四分位差距及滑动标准差等异常值快速判别方法,然后利用含有异常值的清洁天和污染天常规大气污染物(PM_(2.5)、PM_(10)、SO_(2)、NO_(2)、CO和O_(3))时间序列数据对3种异常值判别方法的有效性进行测试评估,从而得到不同污染物异常值判别的最优方法及相关参数指标.结果表明:无论是清洁天还是污染天,滑动四分位法对PM_(2.5)、PM_(10)、SO_(2)、NO_(2)、CO和O_(3)浓度时间序列异常值的判别效果均最优.其中,清洁天最优滑动窗口长度范围分别为10~16、14~16、12~16、38~40、6~38和6~8,最优宽容度常数范围分别为1.6~1.7、1.6~2.6、1.7~2.0、2.3~2.5、1.6~4.5和3.7~3.8;而污染天最优滑动窗口长度范围分别为10~44、10~14、10~32、14~48、10~48和14~20,最优宽容度常数范围分别为2.7~4.5、1.4~2.8、2.8~4.5、2.7~4.5、1.5~4.5和2.5~3.8.清洁天和污染天中不同大气污染物时间序列波动特征不同,使得适用方法的最优参数存在显著差异.本文构建的异常值快速判别方法旨在为环境大数据异常值的快速识别及更准确地分析大气污染成因提供一定技术支撑. | 李艺 华静 刘保双 张裕芬 冯银厂 | 2022 | 环境科学学报2022，42，12： | 2 |
| 10 | 超低排放改造推广及NH_(3)减排对京津冀冬季环境效益研究显示文摘为量化京津冀(BTH)地区超低排放(ULE)改造推广应用潜在的环境效益,基于GEOS-Chem大气化学模型,设计了2个全国情景和6个区域情景,从区域大气输送、超低排放改造在燃煤电厂(CPPs)、工业燃煤(ICB)推广及控制NH;排放等方面进行研究.结果表明:(1)全国燃煤电厂完成ULE改造,使得京津冀地区2015年1月PM_(2.5)浓度下降3.2%(2.4μg·m^(-3)),如只是京津冀地区燃煤电厂完成ULE改造,可使京津冀地区PM_(2.5)浓度降低1.1%(0.8μg·m^(-3)),可知区域联防联控对雾霾的治理具有重要意义;(2)在京津冀地区燃煤电厂完成ULE改造的基础上,工业燃煤完成ULE改造、NH;排放减少30%和50%,可使得京津冀地区PM_(2.5)浓度分别降低5.4%(3.5μg·m^(-3))、4.7%(4.0μg·m^(-3))和7.7%(5.7μg·m^(-3)),可知工业燃煤的ULE改造和NH;减排,均可显著降低PM_(2.5)的浓度;(3)在京津冀地区燃煤电厂和工业燃煤都完成ULE改造的基础上,NH;排放分别减少30%和50%,可使得PM_(2.5)浓度分别降低8.5%(6.3μg·m^(-3))和11.2%(8.3μg·m^(-3)),可知工业燃煤的ULE改造降低常规污染物或NH;减排控制均能显著降低PM_(2.5)浓度,为更好地降低京津冀地区PM_(2.5)的浓度应综合考虑工业燃煤的ULE改造、NH;减排及区域联防联控,可通过经济代价和环境效益分析确定最佳的雾霾治理方案. | 焦小淼 任世华 张伟 刘潇 | 2022 | 环境科学学报2022，42，5： | 1 |
| 11 | Interannual evolution of the chemical composition,sources and processes of PM_(2.5)in Chengdu,China:Insights from observations in four winters显示文摘The air quality in China has improved significantly in the last decade and,correspondingly,the characteristics of PM_(2.5)have also changed.We studied the interannual variation of PM_(2.5)in Chengdu,one of the most heavily polluted megacities in southwest China,during the most polluted season(winter).Our results show that the mass concentrations of PM_(2.5)decreased significantly year-by-year,from 195.8±91.0μg/m~3in winter 2016 to 96.1±39.3μg/m^(3)in winter 2020.The mass concentrations of organic matter(OM),SO_()4^(2-),NH_(4)^(+)and NO_(3)^(-)decreased by 49.6%,57.1%,49.7% and 28.7%,respectively.The differential reduction in the concentrations of chemical components increased the contributions from secondary organic carbon and NO_(3)^(-)and there was a larger contribution from mobile sources.The contribution of OM and NO_(3)^(-)not only increased with increasing levels of pollution,but also increased year-by-year at the same level of pollution.Four sources of PM_(2.5)were identified:combustion sources,vehicular emissions,dust and secondary aerosols.Secondary aerosols made the highest contribution and increased year-by-year,from 40.6%in winter 2016 to 46.3% in winter 2020.By contrast,the contribution from combustion sources decreased from 14.4% to 8.7%.Our results show the effectiveness of earlier pollution reduction policies and emphasizes that priority should be given to key pollutants(e.g.,OM and NO_(3)^(-))and sources(secondary aerosols and vehicular emissions)in future policies for the reduction of pollution in Chengdu during the winter months. | Junke Zhang Jiaqi Li Yunfei Su Chunying Chen Luyao Chen Xiaojuan Huang Fangzheng Wang Yawen Huang Gehui Wang | 2024 | Journal of Environmental Sciences2024，，4： | 0 |
| 12 | Analysis of China’s PM_(2.5)and ozone coordinated control strategy based on the observation data from 2015 to 2020显示文摘The coordinated control of PM_(2.5)and ozone has become the strategic goal of national air pollution control.Considering the gradual decline in PM_(2.5)concentration and the aggravation of ozone pollution,a better understanding of the coordinated control of PM_(2.5)and ozone is urgently needed.Here,we collected and sorted air pollutant data for 337 cities from 2015 to 2020 to explore the characteristics of PM_(2.5)and ozone pollution based on China’s five major air pollution regions.The results show that it is necessary to continue to strengthen the emission reduction in PM_(2.5)and ozone precursors,and control NO_(x) and VOCs while promoting a dramatic emission reduction in PM_(2.5).The primary method of curbing ozone pollution is to strengthen the emission control of VOCs,with a long-term strategy of achieving substantial emission reductions in NO_(x),because VOCs and NO_(x) are also precursors to PM_(2.5);hence,their reductions also contribute to the reduction in PM_(2.5).Therefore,the implementation of a multipollutant emission reduction control strategy aimed at the prevention and control of PM_(2.5)and ozone pollution is the only means to realize the coordinated control of PM_(2.5)and ozone. | Liuwei Kong Mengdi Song Xin Li Ying Liu Sihua Lu Limin Zeng Yuanhang Zhang | 2024 | Journal of Environmental Sciences2024，，4： | 0 |
| 13 | 基于OMI的陕甘宁地区NO_(2)时空分布及影响因素分析显示文摘为获取NO_(2)时空分布特征并探究NO_(2)污染状况,利用臭氧观测仪(OMI)反演的对流层NO_(2)柱浓度数据,并结合气象、能源及交通排放等统计数据,通过地理空间分析、线性拟合、相关性分析等手段,分析了2005―2019年陕甘宁地区NO_(2)柱浓度的时间变化趋势、空间分布特征及其影响因素。结果表明:近15年NO_(2)柱浓度总体呈先上升后下降的趋势;季节上呈现为冬季>秋季>春季>夏季,其中夏季变化平稳,冬季波动剧烈。从空间分布来看,NO_(2)柱浓度较高区域分布在省会及附近区域,以西安城市群集聚现象最为明显。进一步影响因素分析表明,地形与风向对NO_(2)空间分布有一定的综合影响力;气温、降雨量与NO_(2)柱浓度均呈现出明显的负相关,说明高温、降雨对NO_(2)浓度具有削减作用;煤炭消耗量、工业产值、机动车保有量均与NO_(2)柱浓度呈正相关,说明化石能源燃烧、机动车尾气排放是该地区NO_(2)的重要来源;而2012年后的NO_(2)柱浓度持续下降,主要与国家及地方相关政策的强力实施有关。 | 吴雅睿 王虎 王美景 | 2023 | 大气与环境光学学报2023，18，6： | 0 |
| 14 | Evolution in disparity of PM_(2.5)pollution in China显示文摘The spatial disparity of air pollutants is one of the key influential factors for environmental inequality.We quantitatively evaluated the evolution of PM_(2.5)spatial disparity in China during 2013–2020,and investigated the associations between PM_(2.5)spatial disparity and economic indicators.Differences in PM_(2.5)between more-and less-polluted cities declined over time,suggesting decreased absolute disparity.However,the more polluted cities in 2013 remained so in 2017 and 2020,and vice versa,indicating persistent relative disparity.PM_(2.5)pollution levels increased with higher GDP per capita in less-developed areas of China,but such negative effects weakened over time,while economic development tended to promote cleaner air in developed areas of China.Therefore,policies to improve air quality and promote economic development simultaneously are needed in China to reduce the disparity of air pollution and promote all people to enjoy environmental equality. | Su Shi Weidong Wang Xinyue Li Chang Xu Jian Lei Yixuan Jiang Lina Zhang Cheng He Tao Xue Renjie Chen Haidong Kan Xia Meng | 2023 | Eco-Environment & Health2023，2，4： | 0 |
| 15 | 基于多源数据的陕西省PM_(2.5)时空分布特征及成因分析显示文摘习近平总书记在全国生态环境保护大会明确指出“要以空气质量明显改善为刚性要求,强化联防联控,基本消除重污染天气,还老百姓蓝天白云、繁星闪烁”,不断提升“蓝天幸福感”关乎我国生态文明建设,为大气污染防治指明了方向.PM_(2.5)是空气污染程度衡量的主要指标之一,准确认知PM_(2.5)时空分布特征及成因是大气污染治理的基础.本文首先利用陕西省2015—2021年PM_(2.5)浓度的地面站点监测数据与遥感产品数据,分析了PM_(2.5)浓度时空分布特征.然后,利用Mann-Kendall趋势检验方法分析了陕西省PM_(2.5)浓度的年变化趋势和月变化趋势.最后,以污染较为严重的关中平原3个地级市为例,利用拉格朗日混合单粒子轨道模型(HYAPLIT)后向轨迹模型和聚类分析等方法,模拟了PM_(2.5)污染物气团轨迹,并选取西安为典型地区分析了新冠肺炎疫情(COVID-19)期间在人为活动管控对PM_(2.5)浓度的变化影响.结果表明:(1)从空间分布来看,关中平原PM_(2.5)浓度较高,陕南(安康、汉中、商洛)和陕北(榆林、延安)地区PM_(2.5)浓度较低,月平均浓度呈现U型变化规律.(2)通过MannKendall趋势检验分析可知,2015—2021年陕西省PM_(2.5)浓度整体呈下降趋势,按不同月份分析下降趋势发现秋、冬季呈显著降低趋势.(3)由后向轨迹分析可知,西安、咸阳、渭南的春冬季主要受长距离气团影响,夏秋季主要受短距离气团影响.(4)在西安市人口出行强度减少的条件下,与2015—2019年PM_(2.5)浓度月均值相比,2020年COVID-19期间西安2月—4月PM_(2.5)浓度呈降低趋势,2月空气质量明显有好转,PM_(2.5)浓度与2019年同期相比降低17%. | 张丽萍 王旭峰 何映月 张利瑞 罗亚刚 朱培世 潘瑞昇 田丰 王波 张松林 | 2023 | 环境科学学报2023，43，6： | 0 |
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