Pollution In Beijing Research Articles

Analysis of the Jumping Characteristics and Influencing Factors of Ozone Pollution in Beijing

Based on environmental monitoring data and meteorological observation data from 2016 to 2022 in Beijing, combined with backward trajectory clustering and potential source area contribution analysis, the characteristics, meteorological impacts, and potential source areas of ozone (O3) pollution were analyzed. The results showed that there was a total of 41 O3 pollution processes with jumping characteristics in Beijing from 2016 to 2022, with an average of 5.9 times a year. The occurrence time was concentrated in May to July, and the day of the jump (OJD2) was higher than the day before the jump (OJD1). The average value of ρ(O3-8h) was 78.3% higher, and the peak concentration was 78.9% higher. The high O3 concentration zone in the OJD2 region exhibited a characteristic of advancing from south to north. The main reasons for the occurrence of jumped O3 pollution in Beijing could be summarized as local accumulation caused by unfavorable meteorological conditions and regional transmission impact. The occurrence of jump-type ozone pollution was characterized by an increase in southerly wind frequency, temperature rise, pressure decrease, and precipitation decrease. The increase in southerly wind frequency provided conditions for the transport of O3 and its precursors, and rapid photochemical reactions occurred under local high temperatures, with less superimposed precipitation, comprehensively pushing up the ozone concentration level of OJD2. Six air mass transporting pathways were identified through clustering analysis; the air mass from the direction north of OJD2 decreased by 11.2%, whereas the air mass from the south and east directions increased by 6.7% and 4.4%, respectively, with the air masses mainly transmitting over short distances. The ozone concentration corresponding to the south and east directions was relatively high, making a significant contribution to Beijing's pollution. The analysis of potential source areas revealed that the main potential source areas of OJD2 ozone pollution were the central, southern, and eastern parts of Beijing-Tianjin-Hebei, which contributed 82.6% to the pollution trajectory. There was a significant contribution of regional transport during jump-type ozone pollution, and it is necessary to strengthen joint prevention and control in the Beijing-Tianjin-Hebei Region.

Pollution Characteristics and Source Apportionment of Black Carbon Aerosols during Spring in Beijing.

Black carbon (BC) aerosols are important for absorbing aerosols, affecting global climate change and regional air quality, and potentially harming human health. From March to May 2023, we investigated black carbon aerosol levels and air pollution in Beijing. Employing methods such as linear regression, Potential Source Contribution Function (PSCF) and Concentration-Weighted Trajectory (CWT), we analyzed the characteristics and sources of black carbon aerosols in the region. Results indicate that the light absorption coefficients of BC and BrC decrease with increasing wavelength, with BrC accounting for less than 40% at 370 nm. Daily variations in BC and PM2.5 concentrations exhibit similar trends, peaking in March, and BC displays a distinct bimodal hourly concentration structure during this period. Aethalometer model results suggest that liquid fuel combustion contributes significantly to black carbon (1.08 ± 0.71 μg·m-3), surpassing the contribution from solid fuel combustion (0.31 ± 0.2 μg·m-3). Furthermore, the significant positive correlation between BC and CO suggests that BC emissions in Beijing predominantly result from liquid fuel combustion. Potential source area analysis indicates that air masses of spring in Beijing mainly originate from the northwest (40.93%), while potential source areas for BC are predominantly distributed in the Beijing-Tianjin-Hebei region, as well as parts of the Shandong, Shanxi and Henan provinces. Moreover, this study reveals that dust processes during spring in Beijing have a limited impact on black carbon concentrations. This study's findings support controlling pollution in Beijing and improving regional air quality.

Wintertime fine aerosol particles composition and its evolution in two megacities of southern and northern China

Study on fine aerosols composition can help understand the particles formation and is crucial for improving the accuracy of model simulations. Based on field data measured by a Q-ACSM (Quadrupole-Aerosol Chemical Speciation Monitor), we have comprehensively compared the characteristics, evolution, and potential formation mechanisms of the components in NR-PM2.5 during wintertime at two megacities (Beijing and Guangzhou) of southern and northern China. We show that as PM pollution intensifies, the mass fraction of the primary aerosols (e.g., COA, HOA) in PM2.5 in Guangzhou increased, along with a slight decline in proportion of both the secondary organic (SOA) and inorganic (SIA) aerosols; In contrast, in Beijing, the proportion of the SIA ramped up from 28 % to 53 % with the pollution evolution; and the fraction of SOA in total OA also increased due to a substantial increment in the proportion of MO-OOA (from 29 % to 48 %), suggesting a significance of the secondary processes in worsening aerosols pollution in Beijing. Our further analysis demonstrates a leading role of aqueous pathway in the secondary formation of aerosols at the Beijing site, presenting an exponential rising of SIA and SOA with the relative humidity (RH) increase. Compared to Beijing, however, we find that the photochemical oxidation other than aqueous process in Guangzhou plays a more critical role in those secondary aerosols formation. Combined with the Hysplit trajectory model, we identify the high humid conditions in Guangzhou are typically affected by clean marine air masses, explaining the slower response of secondary components to the RH changes. Moreover, the particles in Guangzhou were observed less hygroscopic that is adverse to the aerosol aqueous chemistry. The results provide basis for the precise control of PM pollution in different regions across China and would be helpful in improving model simulations.

Comprehensively exploring the characteristics and meteorological causes of ozone pollution events in Beijing during 2013–2020

Ozone (O3) pollution deteriorated in recent years in Beijing; however, the evolution characteristics and formation mechanism of O3 pollution events (OPEs) lack comprehensive exploration from a long-term perspective. Based on 35-site (Beijing) and multi-city (North China) O3 and meteorological monitoring and reanalysis data, totally 61 OPEs during 2013–2020 were counted in Beijing to reveal their characteristics, the relationship with regional pollution, and meteorological causes. Mild, moderate, and heavy pollution in all OPEs (203 ± 28 μg/m3 for averaged MDA8 O3) accounted for 68.4%, 27.8%, and 3.8% of 291 days, respectively. 78.7% of OPEs were concentrated in May–July. The averaged MDA8 O3 concentration, total days and durations of OPEs increased notably from 2013 to 2020, with a rate of 1.6 μg/m3/yr, 2.7 d/yr, and 0.2 d/yr, respectively. Overall, 90% (53%) of OPEs in Beijing co-occurred with regional pollution covering Beijing-Tianjin-Hebei (North China) under the predominant southerly airflow. Meteorological causes of different levels and spatial distribution of OPEs were explored through multi-scale weather processes. The increasing proportion of southwesterly-westerly synoptic circulation (49%–80%) and mountain-valley breeze (51%–70%), along with enhanced temperature, UV radiation, southerly wind, and temperature inversion and decreased relative humidity, collectively contributed to elevated levels of OPEs. The aforementioned meteorological condition facilitated O3 photochemical reactions, the transport of pollutants, and hindered diffusion. Three spatial types (urban, northern and southern suburban pollution) of OPEs were determined by the intensity and direction of southerly wind. Additionally, daytime O3 pollution elevated the mean peak O3 of nocturnal O3 enhancement events (NOEs) by 31 μg/m3 (41%) mainly induced by convective storms and low-level jets. Our comprehensive investigations of OPEs provide important scientific basis for the precise prediction and control of O3 pollution in Beijing.

Risk Assessment and Source Analysis of Soil Heavy Metal(oid)s Pollution in Beijing, China

Risk Assessment and Source Analysis of Soil Heavy Metal(oid)s Pollution in Beijing, China

Improved biomass burning pollution in Beijing from 2011 to 2018

The prohibition of open straw burning and clean energy transitions, implemented in the last 10 years, resulted in remarkable reductions in ambient biomass burning pollution in Beijing. Here, we present the reduction of biomass burning molecular tracer (i.e., levoglucosan) concentrations using year-long filter sample results collected in Beijing respectively during 2010–2011 and 2017–2018. The annual mean concentrations (95% CI) of levoglucosan during 2010–2011 and 2017–2018 were 0.34 (0.29–0.38) μg m−3 and 0.11 (0.09–0.13) μg m−3, respectively, with a 67% decrease. Compared to 2011, the two traditional open biomass burning episodes in early summer and during the fall post-harvest season disappeared in 2018. Meanwhile, the intensity and duration of biomass burning episodes during the heating season in 2017–2018 was much weaker and shorter than that in 2010–2011. Our results indicate that the implemented clean air action plans were effective in reducing open biomass burning, but the control of biofuel combustion activities during the heating season remains a major challenge in China.

Observations and explicit modeling of summer and autumn ozone formation in urban Beijing: Identification of key precursor species and sources

Due to the complexity and nonlinearity of the ozone (O3) production, it is vital to understand the detailed knowledge of ozone–precursor relationship for the formulation of effective mitigation of surface ozone pollution. In this study, continuous measurements of O3, volatile organic compounds (VOCs), and related parameters were conducted at an urban site of Beijing in the summer and autumn of 2019. The photochemical box model contained the Master Chemical Mechanism (MCMv3.3.1) was used to reveal the detailed information on the photochemical O3 formation. Results show that the average concentration of total VOCs (TVOC) was 31.2 ± 10.7 ppb and 37.8 ± 18.9 ppb during the summer and autumn campaign, respectively, with the largest contribution from alkanes in both seasons, which mainly originated from liquefied petroleum gas (LPG) usage (20.2%–22.6%), gasoline vehicular exhaust (21.0%–21.6%), diesel vehicular exhaust (18.1%–18.3%), solvent usage (20.4%–24.1%), and fuel evaporation (16.4%–17.4%) that identified by positive matrix factorization (PMF) model. Heavy ozone pollution episodes were observed and the net local O3 production rate during summer (EP1) and autumn (EP2) pollution episode was 9.87 ± 0.62 ppbv h−1, and 9.44 ± 1.18 ppbv h−1, respectively, which was both dominated by the reaction between HO2 with NO. The analysis of relative incremental reactivity (RIR) and O3-NOx-VOC isopleth shows that ozone formation was VOC-limited in urban Beijing, with alkenes and aromatics contributed the most to O3 formation in summer and autumn, respectively. In addition, modellings for various emission reduction scenarios were carried out, indicating the reduction of gasoline vehicles emissions in summer and both reduction of gasoline vehicles and solvent usage emissions in autumn is the best measures to efficiently reduce O3 pollution. These results improved our understanding of O3 precursors and their impact on ozone production and provided a more targeted reference for controlling ozone pollution in Beijing.

Vertical evolution of the concentrations and sources of volatile organic compounds in the lower boundary layer in urban Beijing in summer

Exploring the vertical variations in volatile organic compounds (VOCs) in the atmosphere and quantifying the sources of VOCs at different heights can help control atmospheric photochemical pollution in summer. Here, VOCs were vertically detected at three heights (47 m, 200 m and 320 m) along a 325 m tower of the Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, in the mornings (8:00) and afternoons (15:00) from May 19 to June 18, 2021. The VOC concentrations in Beijing in summer were 16.2 ± 5.6 ppbv, 14.7 ± 2.5 ppbv and 14.9 ± 3.8 ppbv at 47 m, 200 m and 320 m, respectively, and alkanes accounted for the largest proportion at all heights (>56%). The vertical gradients of the VOC concentrations and components did not significantly change, which was consistent with the summer observations of other stations in North China in recent years, but these results significantly differed from observations from more than a decade ago. To determine the reason for this, a classification based on atmospheric stability was performed, revealing that the vertical distribution of VOCs was uniform in convective and stable conditions and decreased with increasing height in neutral condition. With the transition of atmospheric stability from neutral to convective to stable, the contributions of fuel combustion sources and solvent use sources gradually increased, while those of biogenic sources and background sources gradually decreased. With increasing height, the contributions of background sources increased, those of biogenic sources, solvent use and gasoline vehicular emissions decreased, and those of fuel combustion and industrial emissions remained basically unchanged. The above results indicated that with air pollution treatment, the potential for reducing emissions of VOCs in Beijing has decreased. Therefore, regional joint prevention and control are the main ways to control VOC pollution in Beijing.

Secondary aerosol formation drives atmospheric particulate matter pollution over megacities (Beijing and Seoul) in East Asia

Atmospheric particulate matter (PM) pollution in Beijing and Seoul is an urgent concern because of the dense population and the role of the capital city. This study aimed to understand haze formation over East Asia during winter by simultaneously measuring the in situ aerosol chemical composition in the two megacities. During the sampling period, a similar pollution situation characterized by extremely low SO2 (approximately 1 ppbv) and high NOx (approximately 20 ppbv) concentrations and secondary inorganic aerosol (SIA)-dominated PM was found in both cities. Nitrate dominated the inorganic components in the submicron particles in both cities and was more pronounced in Seoul than in Beijing. The enhanced SIA mass concentrations during pollution episodes were observed to be associated with an increased local atmospheric oxidation capacity (indicated by O3+NO2=Ox concentration) and ambient relative humidity under similar stagnant weather conditions. Regarding the thermodynamic equilibrium, abundant aerosol liquid water promoted the partitioning of gaseous HNO3 into its particle phase when pollution events occurred. This result emphasized the importance of local secondary aerosol formation for atmospheric PM pollution in East Asian megacities. The box model simulation of nitrate formation indicated that the homogeneous oxidation of NO2 by OH radicals was the major nitrate formation pathway in both megacities. The downward transport of nitrate from the residual layer also significantly contributed to nitrate concentrations. NOx and volatile organic compounds (VOCs) exhibited a non-linear relationship with nitrate formation. Reducing VOCs concentrations was an efficient approach to mitigate nitrate in both megacities. A reduction of more than 50% in NOx concentrations was required for the effective reduction of nitrate. This study highlighted that Beijing and Seoul were experiencing similar PM pollution situations, and nitrate reduction should be considered to improve their air quality.

Characteristics of particulate-bound n-alkanes indicating sources of PM2.5 in Beijing, China

Abstract. The characteristics of n-alkanes and the contributions of various sources of fine particulate matter (PM2.5) in the atmosphere in Beijing were investigated. PM2.5 samples were collected at Minzu University of China between November 2020 and October 2021, and n-alkanes in the samples were analyzed by gas chromatography mass spectrometry. A positive matrix factorization analysis model and source indices (the main carbon peaks, carbon preference indices, and plant wax contribution ratios) were used to identify the sources of n-alkanes, to determine the contributions of different sources, and to explain the differences. The n-alkane concentrations were 4.51–153 ng m−3 (mean 32.7 ng m−3), and the particulate-bound n-alkane and PM2.5 concentrations varied in parallel. There were marked seasonal and diurnal differences in the n-alkane concentrations (p<0.01). The n-alkane concentrations in the different seasons decreased in the order of winter > spring > summer > fall. The mean concentration of each homolog was higher at night than in the day in all seasons. Particulate-bound n-alkanes were supplied by common anthropogenic and biogenic sources, and fossil fuel combustion was the dominant contributor. The positive matrix factorization model results indicated five sources of n-alkanes in PM2.5, which were coal combustion, diesel vehicle emissions, gasoline vehicle emissions, terrestrial plant release, and mixed sources. Vehicle emissions were the main sources of n-alkanes, contributing 57.6 %. The sources of PM2.5 can be indicated by n-alkanes (i.e., using n-alkanes as organic tracers). Vehicle exhausts strongly affect PM2.5 pollution. Controlling vehicle exhaust emissions is key to controlling n-alkanes and PM2.5 pollution in Beijing.

Influence of Urbanization on the Spatial Distribution of Associations Between Air Pollution and Mortality in Beijing, China.

This study investigated the influence of urbanization on the intra-city spatial distribution of associations between air pollution and mortality in Beijing, China. First, we utilized the generalized additive model to establish the exposure-response associations of PM2.5, O3, with nonaccidental and cardiorespiratory mortality between urban and suburban areas. Second, we assessed district-specific air pollution-related mortality and analyzed how these associations were affected by the degree of urbanization. Finally, we analyzed the changes in air pollution-related mortality before and after the enforcement of the Air Pollution Prevention and Control Action Plan (referred to as the Action Plan). The effect estimates of PM2.5 for nonaccidental mortality were 0.20% (95% CI: 0.12-0.28) in urban areas and 0.46% (95% CI: 0.35-0.58) in suburban areas per 10μg/m3 increase in PM2.5 concentrations. The corresponding estimates of O3 were 0.13% (95% CI: -0.04-0.29) in urban areas and 0.34% (95% CI: 0.12-0.56) in suburban areas per 10μg/m3 increase in O3 concentrations; however, the difference between the estimates of O3 in urban and suburban areas was not statistically significant. The district-specific results suggested that the estimated risks increased along with urban vulnerability levels for the effects of PM2.5. Implementing the Action Plan reduced the mortality risks of PM2.5, but the risks of O3 increased in some districts. However, the difference in the estimates between the pre- and post-emission reductions was not statistically significant. Our study indicated that populations living in less urbanized areas are more vulnerable to the adverse effects of air pollution in Beijing, particularly for PM2.5.

Quantitative assessment of the impact of biomass burning episodes on surface solar radiation using machine learning technology: A case study of a pollution event in Beijing

As an important source of pollutants in Beijing, biomass burning (BB) aerosols emitted by BB have a strong absorption and scattering effect on surface solar radiation (SSR). However, the existence of meteorological factors has a powerful impact on the estimation of the BB aerosol radiation effect. In this paper, a deweathered technique based on machine learning is presented to quantitatively isolate the influence of weather conditions from the radiative effect of BB aerosols. Furthermore, the seasonal trend of SSR is constrained by removing the general seasonal changes by the detrending method. The BB event on October 7–11, 2014, in Beijing was used as a case to validate the effectiveness of the proposed method. Experimental results show that meteorological factors aggravate the influence of BB events on SSR. Specifically, during the BB event, meteorological factors led to an additional increase of 10.9% in diffuse radiation and an additional decrease of 17.5%, 13.1%, 181.3%, 9.7% and 86.9% in global radiation, net radiation, horizontal direct radiation, reflected radiation and vertical direct radiation, respectively. After isolating the impact of meteorological factors on SSR in the BB event, we found that the average effects of BB aerosols on global radiation, net radiation, diffuse radiation, horizontal direct solar radiation, reflected radiation and vertical direct solar radiation during the BB event were −35.6 Wm−2 (−3.1 MJm−2day−1), −14.1 Wm−2 (−1.2 MJm−2day−1), 20.7 Wm−2 (1.8 MJm−2day−1), −67.3 Wm−2 (−5.8 MJm−2day−1), −8.9 Wm−2 (−0.8MJm−2day−1), and −132.9 Wm−2 (−11.5 MJm−2day−1), respectively. In conclusion, the weather normalization and detrended methods in this study provide a new idea for the accurate estimation of the impact of aerosols on SSR. This provides a quantitative reference for further understanding the impacts of atmospheric pollution on SSR.

Lockdown effects of the COVID-19 on the spatio-temporal distribution of air pollution in Beijing, China

To prevent the spread of COVID-19, China enacted a series of strict policies, which reduced anthropogenic activities to a near standstill. This provided a precious window to explore its effects on the spatio-temporal distribution of air pollution in Beijing, China. In this study, continuous wavelet transforms and spatial interpolation methods were used to explore the spatiotemporal variations in air pollutants and their lockdown effects. The results indicate that except O3, the annual average concentration of NO2, PM2.5 and SO2 showed a decreasing trend during 2016 and 2019; NO2, PM2.5 and SO2 show a trend of “low in summer and high in winter”; the diurnal variation of NO2 concentration was mainly related to the rush hours of traffic volume, with the first peak at the morning peak (7:00), and then accumulating gradually to second peak (22:00). The continuous wavelet analysis shows that PM2.5, SO2 and NO2 had four primary periods, while O3 only had two primary periods. The high NO2 concentration areas were mainly in Dongcheng, Xicheng, Chaoyang and Fengtai, while the low concentration areas were located in the northern areas, such as Miyun and Huairou; the PM2.5 concentration decreased from south to north; this characteristic presented more obviously in winter. Compared to the pre-lockdown, NO2 and SO2 decreased considerably during lockdown, whereas PM2.5 and O3 increased dramatically. The contribution rates of transportation activities to the NO2, O3, PM2.5 and SO2 were estimated be 9.4 % ∼ 17.2 %, −76.4 % ∼ −42.9 %, −39.5 % ∼ –22.8 % and 5.7 % ∼ 43.7 %, respectively; the contribution rates of industrial activities were 19.9 % ∼ 26.7 %, 7.8 % ∼ 30.9 %, 1.6 % ∼ 36.2 % and −10.5 % ∼ 15.9 %, respectively. Considering meteorological factors, we inferred that pauses in anthropogenic activities indeed help improving air pollution, but it is difficult to offset the impact of extreme weather. These findings can enhance our understanding on the sources of air pollution, and can therefore provide insights on urban air pollution mitigation.

Analysis on the Evolution, Causes, and Countermeasures of Urban Haze Components in Beijing

Based on the results of PM2.5 sources analysis, this paper analyzes the component evolution, formation causes, and governance countermeasures of urban haze in Beijing. The proportion of coal burned in sources of PM2.5 in Beijing has gradually declined, and motor vehicle exhaust has become the largest source of pollution. The formation of haze pollution in Beijing is related to the change in energy structure, the increase in the number of motor vehicles, the increase of urban construction area, and the cross-regional transmission of pollutants in Hebei, Tianjin, and other places. Beijing’s urban haze control measures include reducing vehicle emissions, optimizing industrial structure, adjusting energy structure, building an eco-city, and implementing cross-regional coordinated governance.

Meteorological and chemical controls on surface ozone diurnal variability in Beijing: A clustering-based perspective

This study aimed to reveal the dominant, recurring patterns of surface ozone diurnal cycles in Beijing, their quantitative characteristics, namely, occurrence frequency and transition probability, and their potential linkages to meteorological and chemical processes based on multi-source observations (surface ozone, satellite-based ozone precursors, ground-based and sonde-based meteorological measurements) and reanalyses (ERA5 meteorological and TCR2 chemical reanalyses). By applying K-means clustering, four distinct ozone diurnal patterns (Cluster 1: all-day low anomaly; Cluster 2: nighttime high-daytime low anomaly; Cluster 3: nighttime low-daytime high anomaly; Cluster 4: extreme pollution pattern with all-day high anomaly) are objectively identified from 2013 to 2020 warm-season (May–September) surface ozone measurements. Despite a relatively low total occurrence, the extreme pollution pattern tended to persist over an extended period (average persistence of 2.3 days). Composite analyses of multi-source meteorology indicate that the elevated nocturnal ozone in Cluster 2 is associated with the compensating downdraft flow of nocturnal convective storms. By contrast, elevated nocturnal ozone in Cluster 4 was associated with the prevailing low-level jet (LLJ) over the whole North China Plain (NCP) region. The LLJ-related dynamical processes trigger regional transport in the residual layer and downward mixing from the residual layer, elevating the background ozone level in downstream Beijing. Moreover, Cluster 4 is under the control of 500-hPa anomalous high pressure, which leads to daytime hot-dry weather favoring the occurrence of extreme afternoon pollution via photochemical ozone production. From Cluster 1 to Cluster 4, satellite-based formaldehyde (CH2O) increased by 71% accompanied by less change in nitrogen dioxide (NO2), causing a shift in ozone production sensitivity. Because extreme pollution pattern typically occurs in the transition regime, synergetic emission control of volatile organic compounds (VOCs) and nitrogen oxides (NOx) would be effective in alleviating severe ozone pollution in Beijing.

Differentiating the Contributions of Particle Concentration, Humidity, and Hygroscopicity to Aerosol Light Scattering at Three Sites in China

AbstractThe scattering of light by aerosol particles dictates atmospheric visibility, which is a straightforward indicator of air quality. It is affected by numerous factors, such as particle number size distribution, particle mass concentration (PM2.5), ambient relative humidity (RH), and chemical composition. The latter two factors jointly influence the aerosol liquid water content (ALWC). Here, the particle backscattering coefficient (βp) under ambient RH conditions is investigated to differentiate and quantify the contributions of aerosol properties and meteorology using comprehensive observational datasets acquired at three megacities in China, that is, Beijing (BJ), Nanjing (NJ), and Guangzhou (GZ). Overall, the temporal variations in βp under ambient RH conditions are consistent with those in ALWC at the three sites. The PM2.5 in BJ is systematically higher than in NJ and GZ, while ambient RH and aerosol hygroscopicity in NJ are much higher than in BJ and GZ. Notable differences in the variations of βp with related factors at the three sites are demonstrated. βp is more sensitive to particle hygroscopicity and mass in NJ and ambient RH in BJ. The relative contributions of these factors to βp at the three sites under different pollution conditions are differentiated and quantified. The factor with the largest impact on the variability in βp shifts from particle mass to ambient RH as air quality deteriorated to heavy pollution in BJ. The opposite is true in NJ. In GZ, the contributions of these factors to changes in βp under different pollution conditions are similar, both dominated by PM2.5.

The Correlation Between Temperature Inversion and Atmosphere Pollution in Beijing

This study aimed to evaluate the correlation between temperature inversion and air pollution in Beijing, China in year 2020. The study first analyzed the monthly trend of temperature inversion levels in 2020, finding that it has two peaks in April and October and has the lowest value in August. The writer used line charts and linear regression method to study the correlation between temperature inversion level and the daily AQI level in Beijing in 2020. The study also focused on the relationship between concentration of polluting air particles: PM2.5, PM10, SO2, CO, NO2 and temperature inversion level, finding that temperature inversion level is positively correlated with the concentration of most polluting particles. The study provided comments for governments and citizens on how to reduce the effect of the air pollution caused by temperature inversion.

The impacts of urban anthropogenic heat and surface albedo change on boundary layer meteorology and air pollutants in the Beijing-Tianjin-Hebei region

In this study, present and future anthropogenic heat flux (AH) and surface albedo (SA) in Beijing are estimated and incorporated into the WRF-Chem/UCM model. A series of nested model simulations are conducted at 9 km and 27 km horizontal grid resolution with 30 layers in the vertical to explore the sensitivity of model results to urban surface characteristics during the study period from 23 February to 13 March 2014, and the impacts of anthropogenic heat and surface albedo changes in the future on urban meteorology and air pollutants in Beijing. Model validation demonstrates that the model with the up-to-date urban surface parameters apparently improves predictions for both meteorological variables and chemical species compared with model results with default urban parameters. The combined effect of SA increase and AH decrease leads to consistent decreases in T2 (air temperature at 2 m above ground), WS10 (wind speed at 10 m) and PBLH (planetary boundary layer height) by up to 1.2 °C, 0.4 m s−1 and 200 m (33%), respectively, in Beijing averaged over the study period. In response to the meteorological changes, near surface PM2.5 (particulate matter with aerodynamic equivalent diameter below 2.5 μm) concentration increases by up to 15.6 μg m−3 (8.6%), whereas O3 concentration decreases by 2.6 ppb (25.1%), respectively. In daytime, near surface cooling due to SA increase and AH decrease causes a strong downdraft over Beijing urban areas, a wind divergence near the surface and an upslope wind over the western mountain, resulting in aerosol transport from urban district to western mountain slope. At nighttime, surface cooling is weaker than that in daytime, leading to a weaker downdraft over Beijing and a slight downslope wind in the mountain. The combined changes in SA and AH lead to a decrease in T2 by 1.2 °C, a decrease of O3 concentration by approximately 20%, and increases in PM2.5 and its components by 10–17% in daytime averaged over the urban areas of Beijing during the study period, and the above changes are weaker during haze days than those in clean days. The changes in urban surface parameters in Beijing in the future may be benefit for mitigating heat wave and O3 pollution risks, but could increase fine aerosol level and human health risk, which require an optimal strategy for co-benefits of climate change mitigation and air pollution control in future city planning.

Retrieval of aerosol optical depth from GF-6 wide field of view 16-m data based on deep blue algorithm

Aerosol optical depth (AOD) is an important indicator for air pollution monitoring. We obtain AOD from the GF-6 satellite, which was launched on June 2, 2018 by China. Beijing is selected as the study area. Based on the deep blue algorithm, the moderate-resolution imaging spectroradiometer surface reflectance product is used to correct and establish the surface reflectance library, and the AOD is retrieved from the GF-6 wide field of view (WFV) blue band. So, the application of the deep blue algorithm in a GF-6 WFV camera is realized. The aerosol is divided into three models: a custom model, a continental model, and an urban model in second simulation of the satellite signal in the solar spectrum model. To improve the accuracy of retrieval results, we recalculated the aerosol component concentration ratio based on GF-6 WFV data and ground observation as the custom model. The retrieval results of the three aerosol models show that the central and southern urban areas are higher than the mountainous areas in the northwest, indicating that human emission is the main source of air pollution in Beijing. The retrieval results of the custom model, continental model, and urban model are compared with the ground observation. The error of urban model retrieval is large, and the determination coefficient R2 is only 0.3671. The results of the custom model and continental model are similar. The R2 of the custom is 0.8942, which is higher than that of the continental (0.8872). We analyze the relationship between the retrieved AOD of the three aerosol models and top of atmosphere (TOA) reflectance and find that the custom AOD has the best sensitivity to TOA reflectance, whereas the urban AOD has the worst sensitivity. So, the custom aerosol model is closer to the real aerosol situation in Beijing.

Measurement report: Ambient volatile organic compound (VOC) pollution in urban Beijing: characteristics, sources, and implications for pollution control

Abstract. The increasing ozone (O3) pollution and high fraction of secondary organic aerosols (SOA) in fine particle mass has highlighted the importance of volatile organic compounds (VOCs) in air pollution control. In this work, four intensive field measurements of VOCs during winter of 2018 (from 1 December 2018 to 17 January 2019), spring (15 April to 27 May), summer (17 June to 13 July), and autumn (22 September to 27 November) of 2019 were conducted at an urban site in Beijing to characterize VOC sources and their contributions to air pollution. The total mixing ratio of the 95 quantified VOCs (TVOC) observed in this study ranged from 5.5–118.7 ppbv with the mean value of 34.9 ppbv. Alkanes, OVOCs, and halocarbons were the dominant chemical groups, accounting for 75 %–81 % of the TVOC across the sampling months. The molar ratios of VOCs to NOx indicated that O3 formation was limited by VOCs during the whole sampling period. Positive matrix factorization (PMF) analysis showed that diesel vehicle exhaust, gasoline vehicle exhaust, and industrial emissions were the main VOC sources during both the O3-polluted and PM2.5-polluted months. On the basis of O3 formation impact, VOCs from fuel evaporation and diesel exhaust, particularly toluene, xylenes, trans-2-butene, acrolein, methyl methacrylate, vinyl acetate, 1-butene, and 1-hexene, were the main contributors, illustrating the necessity of conducting emission controls on these pollution sources and species to alleviate O3 pollution. Instead, VOCs from diesel exhaust as well as coal and biomass combustion were found to be the dominant contributors to secondary organic aerosol formation potential (SOAFP), particularly the VOC species of toluene, 1-hexene, xylenes, ethylbenzene, and styrene, and top priority should be given to these for the alleviation of haze pollution. This study provides insights for the government to formulate effective VOC control measures for air pollution in Beijing.