Prediction of daily PM2.5 and ozone based on high-density weather stations in China: Nonlinear effects of meteorology, human and ecosystem health risks

[1]  Yunsoo Choi,et al.  Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter. , 2022, Environmental pollution.

[2]  Tao Wang,et al.  Ground-level ozone pollution in China: a synthesis of recent findings on influencing factors and impacts , 2022, Environmental Research Letters.

[3]  Yusef Omidi Khaniabadi,et al.  Ozone modellingand mapping for risk assessment: An overview of different approaches for human and ecosystems health. , 2022, Environmental research.

[4]  D. Wardle,et al.  Suppression of Ozone Formation at High Temperature in China: From Historical Observations to Future Projections , 2022, Geophysical Research Letters.

[5]  Congbo Song,et al.  Revealing Drivers of Haze Pollution by Explainable Machine Learning , 2022, Environmental Science & Technology Letters.

[6]  Yuesi Wang,et al.  Air stagnation in China: Spatiotemporal variability and differing impact on PM2.5 and O3 during 2013-2018. , 2022, The Science of the total environment.

[7]  Yansen Xu,et al.  Ozone pollution threatens the production of major staple crops in East Asia , 2022, Nature Food.

[8]  Q. Xiao,et al.  Tracking PM2.5 and O3 Pollution and the Related Health Burden in China 2013-2020. , 2021, Environmental science & technology.

[9]  Q. Xiao,et al.  Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multisource Data Fusion. , 2021, Environmental science & technology.

[10]  Xiong Liu,et al.  Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China , 2021, Remote Sensing of Environment.

[11]  J. Seinfeld,et al.  Large scale control of surface ozone by relative humidity observed during warm seasons in China , 2021, Environmental Chemistry Letters.

[12]  Shuiyuan Cheng,et al.  Influencing factors of PM2.5 and O3 from 2016 to 2020 based on DLNM and WRF-CMAQ. , 2021, Environmental pollution.

[13]  X. Yue,et al.  A humidity-based exposure index representing ozone damage effects on vegetation , 2021 .

[14]  G. Carmichael,et al.  A 6-year-long (2013–2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC , 2021 .

[15]  Junying Sun,et al.  Robust prediction of hourly PM2.5 from meteorological data using LightGBM , 2021, National science review.

[16]  L. Emberson.  Effects of ozone on agriculture, forests and grasslands , 2020, Philosophical Transactions of the Royal Society A.

[17]  J. Schwartz,et al.  An ensemble learning approach for estimating high spatiotemporal resolution of ground-level ozone in the contiguous United States. , 2020, Environmental science & technology.

[18]  Zifa Wang,et al.  Health impacts of long-term ozone exposure in China over 2013-2017. , 2020, Environment international.

[19]  A. Russell,et al.  Air Pollutant Correlations in China: Secondary Air Pollutant Responses to NOx and SO2 Control , 2020 .

[20]  G. Hoek,et al.  Long-term exposure to PM and all-cause and cause-specific mortality: A systematic review and meta-analysis. , 2020, Environment international.

[21]  Zifa Wang,et al.  Affinity zone identification approach for joint control of PM2.5 pollution over China. , 2020, Environmental pollution.

[22]  Yang Liu,et al.  Spatiotemporal distributions of surface ozone levels in China from 2005 to 2017: A machine learning approach. , 2020, Environment international.

[23]  Zemin Wang,et al.  Construction of a virtual PM2.5 observation network in China based on high-density surface meteorological observations using the Extreme Gradient Boosting model. , 2020, Environment international.

[24]  H. Fu,et al.  Developing a novel hybrid model for the estimation of surface 8 h ozone (O3) across the remote Tibetan Plateau during 2005–2018 , 2020 .

[25]  D. Qin,et al.  PM2.5 and O3 pollution during 2015-2019 over 367 Chinese cities: Spatiotemporal variations, meteorological and topographical impacts. , 2020, Environmental pollution.

[26]  Lin Sun,et al.  Improved 1 km resolution PM2.5 estimates across China using enhanced space–time extremely randomized trees , 2020 .

[27]  J. Xin,et al.  An analysis of the effects of weather and air pollution on tropospheric ozone using a generalized additive model in Western China: Lanzhou, Gansu , 2020 .

[28]  T. Petäjä,et al.  Contrasting trends of PM2.5 and surface-ozone concentrations in China from 2013 to 2017 , 2020, National science review.

[29]  Zifa Wang,et al.  Retrieval of surface PM2.5 mass concentrations over North China using visibility measurements and GEOS-Chem simulations , 2020, Atmospheric Environment.

[30]  Jane Liu,et al.  Local and synoptic meteorological influences on daily variability in summertime surface ozone in eastern China , 2020 .

[31]  Tao Song,et al.  Quantifying the impact of synoptic circulation patterns on ozone variability in northern China from April to October 2013–2017 , 2019 .

[32]  Yuesi Wang,et al.  Exploring the regional pollution characteristics and meteorological formation mechanism of PM2.5 in North China during 2013-2017. , 2019, Environment international.

[33]  Zhao-Yue Chen,et al.  Using Bayesian spatio-temporal model to determine the socio-economic and meteorological factors influencing ambient PM2.5 levels in 109 Chinese cities. , 2019, Environmental pollution.

[34]  J. Hao,et al.  Trends in particulate matter and its chemical compositions in China from 2013–2017 , 2019, Science China Earth Sciences.

[35]  Qian Du,et al.  A Full-Coverage Daily Average PM2.5 Retrieval Method with Two-Stage IVW Fused MODIS C6 AOD and Two-Stage GAM Model , 2019, Remote. Sens..

[36]  Qiang Zhang,et al.  Exploring 2016–2017 surface ozone pollution over China: source contributions and meteorological influences , 2019, Atmospheric Chemistry and Physics.

[37]  Renhe Zhang,et al.  The Effects of PM2.5 Concentrations and Relative Humidity on Atmospheric Visibility in Beijing , 2019, Journal of Geophysical Research: Atmospheres.

[38]  Changqing Lin,et al.  Analysis of the adverse health effects of PM2.5 from 2001 to 2017 in China and the role of urbanization in aggravating the health burden. , 2019, The Science of the total environment.

[39]  Zifa Wang,et al.  Probabilistic Automatic Outlier Detection for Surface Air Quality Measurements from the China National Environmental Monitoring Network , 2018, Advances in Atmospheric Sciences.

[40]  L. Knibbs,et al.  A machine learning method to estimate PM2.5 concentrations across China with remote sensing, meteorological and land use information. , 2018, The Science of the total environment.

[41]  Jiaren Sun,et al.  The impact of synoptic circulation on air quality and pollution-related human health in the Yangtze River Delta region. , 2017, The Science of the total environment.

[42]  Miaomiao Liu,et al.  Visibility-Based PM2.5 Concentrations in China: 1957-1964 and 1973-2014. , 2017, Environmental science & technology.

[43]  Lei Huang,et al.  Development of land use regression models for PM2.5, SO2, NO2 and O3 in Nanjing, China , 2017, Environmental research.

[44]  Robert E. Dickinson,et al.  PM2.5 Pollution in China and How It Has Been Exacerbated by Terrain and Meteorological Conditions , 2017 .

[45]  Sumit Sharma,et al.  Photo-chemical transport modelling of tropospheric ozone: A review , 2017 .

[46]  R. Garcia-Herrera,et al.  Spatial clustering and meteorological drivers of summer ozone in Europe , 2017 .

[47]  N. Unger,et al.  Ozone and haze pollution weakens net primary productivity in China , 2016 .

[48]  Tao Song,et al.  The observation‐based relationships between PM2.5 and AOD over China , 2016 .

[49]  H. Kan,et al.  Long-term trend and spatial pattern of PM2.5 induced premature mortality in China. , 2016, Environment international.

[50]  L. Olcese,et al.  A Method to Improve MODIS AOD Values: Application to South America , 2016 .

[51]  Daniel Krewski,et al.  Long-Term Ozone Exposure and Mortality in a Large Prospective Study. , 2016, American journal of respiratory and critical care medicine.

[52]  Hong-Lei Yang,et al.  Estimating PM2.5 Concentrations in Xi'an City Using a Generalized Additive Model with Multi-Source Monitoring Data , 2015, PloS one.

[53]  Kevin W. Bowman,et al.  Toward the next generation of air quality monitoring: Ozone , 2013 .

[54]  Wei Huang,et al.  Systematic review of Chinese studies of short-term exposure to air pollution and daily mortality. , 2013, Environment international.

[55]  Judith C. Chow,et al.  Impacts of aerosol compositions on visibility impairment in Xi'an, China , 2012 .

[56]  G. Mills,et al.  New stomatal flux-based critical levels for ozone effects on vegetation , 2011 .

[57]  I. Barmpadimos,et al.  Influence of meteorology on PM 10 trends and variability in Switzerland from 1991 to 2008 , 2010 .

[58]  Pat Dolwick,et al.  The effects of meteorology on ozone in urban areas and their use in assessing ozone trends , 2007 .

[59]  S. Beevers,et al.  Modelling and assessing trends in traffic-related emissions using a generalised additive modelling approach , 2007 .

[60]  Prabir Burman,et al.  Estimation of generalized additive models , 1990 .

[61]  Danlu Chen,et al.  Understanding the causal influence of major meteorological factors on ground ozone concentrations across China , 2020 .

[62]  P. Brimblecombe,et al.  Ozone pollution in China: A review of concentrations, meteorological influences, chemical precursors, and effects. , 2017, The Science of the total environment.

[63]  Delong Zhao,et al.  Effects of meteorology and secondary particle formation on visibility during heavy haze events in Beijing, China. , 2015, The Science of the total environment.

[64]  H. Liao,et al.  Climatic effects of air pollutants over china: A review , 2014, Advances in Atmospheric Sciences.