Evaluation and Evolution of MAX-DOAS-observed Vertical NO_(2) Profiles in Urban Beijing

Multiaxis differential absorption spectroscopy(MAX-DOAS)is a newly developed advanced vertical profile detection method,but the vertical nitrogen dioxide(NO_(2))profiles measured by MAX-DOAS have not yet been fully verified.In this study,we perform MAX-DOAS and tower gradient observations to simultaneously acquire tropospheric NO_(2)observations in the Beijing urban area from 1 April to 31 May 2019.The average values of the tropospheric NO_(2)vertical column densities measured by MAX-DOAS and the tropospheric monitoring instrument are 15.8×1015 and 12.4×1015 molecules cm−2,respectively,and the correlation coefficient R reaches 0.87.The MAX-DOAS measurements are highly consistent with the tower-based in situ measurements,and the correlation coefficients R from the ground to the upper air are 0.89(60 m),0.87(160 m),and 0.76(280 m).MAX-DOAS accurately measures the trend of NO_(2)vertical profile changes,although a large underestimation occurs by a factor of two.By analyzing the NO_(2)vertical profile,the NO_(2)concentration reveals an exponential decrease with height.The NO_(2)vertical profile also coincides with the evolution of the boundary layer height.The study shows that the NO_(2)over Beijing mainly originates from local sources and occurs in the boundary layer,and its vertical evolution pattern has an important guiding significance to better understand nitrate production and ozone pollution.

Characteristics of PM_(2.5) pollution in Beijing after the improvement of air quality

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.

Annual nonmethane hydrocarbon trends in Beijing from 2000 to 2019

High loads of ground-level ozone have occurred with the implementation of the Air Pollution Prevention and Control Action Plan.However,the long temporal variation in precursor nonmethane hydrocarbons(NMHCs)has rarely been studied.In this study,we examined the evolution of NMHCs in Beijing based on ambient measurements from 2000 to 2019.The results indicated that the annual variation of ambient NMHCs during 2000 and 2019 could be divided into two stages.The mixing ratios of NMHCs rapidly rose during 2000 and 2009(1.76 ppbv/year)but exhibited a downward trend from 2009 to 2019 at rate of 0.80 ppbv/yr.Moreover,the notable decrease in alkenes and aromatics after 2009 led to a sharp decrease in the propylene-equivalent concentration(PEC)(-0.80 ppbv/year).Implementation of emission reduction measures in Beijing have effectively reduced the contribution of vehicle-related sources,but the contribution of solvent usage and fuel consumption increased,which will become the focus of VOC control in Beijing in the future.

Understand the local and regional contributions on air pollution from the view of human health impacts

The source-receptor matrix of PM_(2.5)concentration from local and regional sources in the Beijing-Tianjin-Hebei(BTH)and surrounding provinces has been created in previous studies.However,because the spatial distribution of concentration does not necessarily match with that of the population,such concentration-based source-receptor matrix may not fully reflect the importance of pollutant control effectiveness in reducing the PM_(2.5)-related health impacts.To demonstrate that,we study the source-receptor matrix of the PM_(2.5)-related deaths instead,with inclusion of the spatial correlations between the concentrations and the population.The advanced source apportionment numerical model combined with the integrated exposure-response functions is used for BTH and surrounding regions in 2017.We observed that the relative contribution to PM_(2.5)-related deaths of local emissions was 0.75%to 20.77%larger than that of PM_(2.5)concentrations.Such results address the importance of local emissions control for reducing health impacts of PM_(2.5)particularly for local residents.Contribution of regional transport to PM_(2.5)-related deaths in rural area was 22%larger than that in urban area due to the spatial pattern of regional transport which was more related to the rural population.This resulted in an environmental inequality in the sense that people staying in rural area with access to less educational resources are subjected to higher impacts from regional transport as compared with their more resourceful and knowledgeable urban compatriots.An unexpected benefit from the multi-regional joint controls is suggested for its effectiveness in reducing the regional transport of PM_(2.5)pollution thus mitigating the associated environmental inequality.