Corrigendum to “Drivers of PM_(2.5)-O_(3) co-pollution: from the perspective of reactive nitrogen conversion pathways in atmospheric nitrogen cycling” [Sci. Bull. 67(18) (2022) 1833–1836]

The authors would like to correct Fig.1e,f.Due to our neglect when doing the picture layout of Fig.1,the abscissa in Fig.1e,f is error:the abscissa ranges from
80 to 0 in Fig.1e and ranges from
90 to
20 in Fig.1f.The image has been corrected:the abscissa ranges from
80 to 80 in Fig.1e and ranges from
80 to 80 in Fig.1f[1].We declare that this correction does not change the results or conclusions of this paper.

Impacts of meteorology and precursor emission change on O_(3) variation in Tianjin, China from 2015 to 2021

Deterioration of surface ozone (O_(3)) pollution in Northern China over the past few years received much attention.For many cities,it is still under debate whether the trend of surface O_(3)variation is driven by meteorology or the change in precursors emissions.In this work,a time series decomposition method (Seasonal-Trend decomposition procedure based on Loess (STL)) and random forest (RF) algorithm were utilized to quantify the meteorological impacts on the recorded O_(3)trend and identify the key meteorological factors affecting O_(3)pollution in Tianjin,the biggest coastal port city in Northern China.After “removing” the meteorological fluctuations from the observed O_(3)time series,we found that variation of O_(3)in Tianjin was largely driven by the changes in precursors emissions.The meteorology was unfavorable for O_(3)pollution in period of 2015-2016,and turned out to be favorable during 2017-2021.Specifically,meteorology contributed 9.3μg/m^(3)O_(3)(13%) in 2019,together with the increase in precursors emissions,making 2019 to be the worst year of O_(3)pollution since 2015.Since then,the favorable effects of meteorology on O_(3)pollution tended to be weaker.Temperature was the most important factor affecting O_(3)level,followed by air humidity in O_(3)pollution season.In the midday of summer days,O_(3)pollution frequently exceeded the standard level (>160μg/m^(3)) at a combined condition with relative humidity in 40%-50%and temperature>31℃.Both the temperature and the dryness of the atmosphere need to be subtly considered for summer O_(3)forecasting.

New insights into the formation of ammonium nitrate from a physical and chemical level perspective

High levels of fine particulate matter(PM_(2.5))is linked to poor air quality and premature deaths,so haze pollution deserves the attention of the world.As abundant inorganic components in PM_(2.5),ammonium nitrate(NH_(4)NO_(3))formation includes two processes,the diffusion process(molecule of ammonia and nitric acid move from gas phase to liquid phase)and the ionization process(subsequent dissociation to form ions).In this study,we discuss the impact of meteorological factors,emission sources,and gaseous precursors on NH4NO3 formation based on thermodynamic theory,and identify the dominant factors during clean periods and haze periods.Results show that aerosol liquid water content has a more significant effect on ammonium nitrate formation regardless of the severity of pollution.The dust source is dominant emission source in clean periods;while a combination of coal combustion and vehicle exhaust sources is more important in haze periods.And the control of ammonia emission is more effective in reducing the formation of ammonium nitrate.The findings of this work inform the design of effective strategies to control particulate matter pollution.

Impact of meteorological condition changes on air quality and particulate chemical composition during the COVID-19 lockdown

Stringent quarantine measures during the Coronavirus Disease 2019(COVID-19)lockdown period(January 23,2020 to March 15,2020)have resulted in a distinct decrease in anthropogenic source emissions in North China Plain compared to the paralleled period of 2019.Particularly,22.7%decrease in NO_(2)and 3.0%increase of O_(3)was observed in Tianjin,nonlinear relationship between O_(3)generation and NO_(2)implied that synergetic control of NOx and VOCs is needed.Deteriorating meteorological condition during the COVID-19 lockdown obscured the actual PM2.5 reduction.Fireworks transport in 2020 Spring Festival(SF)triggered regional haze pollution.PM2.5 during the COVID-19 lockdown only reduced by 5.6%in Tianjin.Here we used the dispersion coefficient to normalize the measured PM2.5(DN-PM2.5),aiming to eliminate the adverse meteorological impact and roughly estimate the actual PM2.5 reduction,which reduced by 17.7%during the COVID-19 lockdown.In terms of PM2.5 chemical composition,significant NO_(3)−increase was observed during the COVID-19 lockdown.However,as a tracer of atmospheric oxidation capacity,odd oxygen(Ox=NO_(2)+O_(3))was observed to reduce during the COVID-19 lockdown,whereas relative humidity(RH),specific humidity and aerosol liquid water content(ALWC)were observed with noticeable enhancement.Nitrogen oxidation rate(NOR)was observed to increase at higher specific humidity and ALWC,especially in the haze episode occurred during 2020SF,high air humidity and obvious nitrate generation was observed.Anomalously enhanced air humidity may response for the nitrate increase during the COVID-19 lockdown period.

Machine learning and theoretical analysis release the non-linear relationship among ozone,secondary organic aerosol and volatile organic compounds

Fine particulate matter(PM_(2.5))and ozone(O_(3))pollutions are prevalent air quality issues in China.Volatile organic compounds(VOCs)have significant impact on the formation of O_(3)and secondary organic aerosols(SOA)contributing PM_(2.5).Herein,we investigated 54 VOCs,O_(3)and SOA in Tianjin from June 2017 to May 2019 to explore the non-linear relationship among O_(3),SOA and VOCs.The monthly patterns of VOCs and SOA concentrations were characterized by peak values during October to March and reached a minimum from April to September,but the observed O_(3)was exactly the opposite.Machine learning methods resolved the importance of individual VOCs on O_(3)and SOA that alkenes(mainly ethylene,propylene,and isoprene)have the highest importance to O_(3)formation;alkanes(C_(n),n≥6)and aromatics were the main source of SOA formation.Machine learning methods revealed and emphasized the importance of photochemical consumptions of VOCs to O_(3)and SOA formation.Ozone formation potential(OFP)and secondary organic aerosol formation potential(SOAFP)calculated by consumed VOCs quantitatively indicated that more than 80%of the consumed VOCs were alkenes which dominated the O_(3)formation,and the importance of consumed aromatics and alkenes to SOAFP were 40.84%and 56.65%,respectively.Therein,isoprene contributed the most to OFP at 41.45%regardless of the season,while aromatics(58.27%)contributed the most to SOAFP in winter.Collectively,our findings can provide scientific evidence on policymaking for VOCs controls on seasonal scales to achieve effective reduction in both SOA and O_(3).

从大气氮循环中活性氮转化途径的角度谈PM_(2.5)-O_(3)复合污染的驱动因素

Fine particulate matter(PM)and ozone(O),two globally signifcant air pollutants,have exerted substantial adverse impacts on climate and human health[1].From 2013 to 2020,China has achieved a signifcant decline of PMlevels,though O3pollution has deteriorated over time[2].PM-Oco-pollution includes not only both high levels of PMand O,but also high PMor Oeven when the other remain low.Therefore,the coordinated control of PMand Oshould not only focus on reducing high concentrations of PMand Osimultaneously.