To study the atmospheric quality status of Wuhan City, three sampling points were set up in ID (Industrial Zone), DT (Central Urban Area), and BG (Botanical Garden). PM2.5 (Fine Particle Matter) samples in the atmosphere were collected synchronously for one year, and the mass concentration, source, and health risks of PAHs (Polycyclic Aromatic Hydrocarbons) were studied. The results showed that the ID, DT, and BG sampling points in Wuhan City ρ The average annual values of (PAHs) were (75.60 ± 28.12) (59.77 ± 22.81) (24.27 ± 9.15) ng/m3, respectively, and showed a seasonal trend of highest in winter and lowest in summer. PMF (Positive Definite Matrix Factor Analysis) results showed that the main sources of PAHs at ID, DT, and BG sampling points were coal and dust (35% and 33%), motor vehicles and dust (30% and 34%), motor vehicles and wood combustion (33% and 32%), respectively, Dust contributes significantly to PAHs in atmospheric particulate matter, with coal burning and wood burning being important sources of PAHs at ID and BG sampling points, respectively. Among the three sampling points, motor vehicles contribute significantly to PAHs in particulate matter, especially at DT and BG sampling points, with motor vehicles contributing more than 30%. Backward trajectory models are used to analyze the source of air masses in Wuhan during the sampling period, and combined with daily ρ (PAHs) found that different clusters of air masses correspond to ρ The difference in PAHs is very small, indicating that regional transmission has little contribution to PAHs in Wuhan. Through the assessment of PAHs inhalation risk in atmospheric particulate matter in Wuhan, it was found that the inhalation risk range of PAHs in Wuhan is between 10-7 and 10-5, and some populations at ID and DT sampling points have slightly higher inhalation risk than the safe range (below 10-6), indicating a potential carcinogenic risk
Research Area ρ The relationship between the spatiotemporal distribution characteristics of (PM2.5) and the types of polluted weather is one of the key supporting technologies for air pollution prevention and control, as well as air quality prediction and early warning. Based on the daily monitoring data and related meteorological data of environmental air quality in 14 cities in Guangxi from 2015 to 2016, the air quality overview and basic characteristics of pollution in Guangxi from 2015 to 2016 were analyzed. EOF (empirical orthogonal function) analysis and backward trajectory clustering analysis were used to characterize Guangxi ρ (PM2.5) spatiotemporal distribution mode was used to analyze 24 regional atmospheric mild and above pollution processes (3 or more contiguous cities) in Guangxi over the past two years. The weather types and air quality variation characteristics of different pollution processes were analyzed. The results showed that PM2.5 was the primary pollutant in atmospheric pollution in Guangxi, ρ The average annual value of (PM2.5) shows a regional characteristic of high in the north and low in the south, and the monthly variation basically shows a positive V-shaped distribution; EOF analysis and backward trajectory clustering analysis show that Guangxi ρ The spatiotemporal structure of (PM2.5) mainly has three modes, with variance contribution rates of 78.9%, 5.7%, and 3.7%, respectively, which basically reflects Guangxi ρ The main characteristics of the spatiotemporal mode of (PM2.5) change, and the backward trajectory clustering between Guilin and Yulin in two years well explained the anti phase distribution characteristics of the north-south concentration and east-west concentration anomalies of the second and third modes; There are 10 main types of PM2.5 regional pollution weather in 14 cities in Guangxi over the past two years. Among them, the main types of pollution weather are weak cold high pressure ridge type (24.4%), uniform pressure field type (20.2%), high pressure rear type (16.1%), and high pressure rear combined with southwest warm low pressure type (8.5%), which are typical weather types that cause large-scale air pollution in Guangxi. Research shows that air pollution in Guangxi has regional, seasonal, and north-south transport characteristics, The weather situation changes during the pollution process have certain regularity
Atmospheric particulate matter contains multiple components of aerosols, among which carbon aerosols have received increasing attention due to their significant impact on human health and visibility. To study the long-term changes of carbon aerosols, PM10 samples from Chengdu from 2009 to 2013 were collected and their inorganic elements, water-soluble ions, and carbon components were measured, And the "PMF (Positive Definite Matrix Factorization) Ratio" model was used to analyze the sources of PM10 and the carbon aerosols contained in it. The results showed that the carbon aerosol concentrations were higher in January, February, May, and December, with higher OC/EC (organic carbon to elemental carbon mass concentration ratio) in January, February, and December, and the PMF Ratio model calculation results also showed an increase in winter SOC, Indicating that there may be more secondary organic carbon (SOC) generation in winter; In May, the char EC/soot-EC (mass concentration ratio of char EC=EC1-OP, soot-EC=EC2+EC3, which can better distinguish source types) was higher, and the K content was also higher, indicating that there may be more biomass combustion emissions. PM10 analysis revealed a total of 6 types of sources, followed by crustal dust (26.5%), secondary sulfate (25.1%), coal and biomass combustion mixed sources (17.3%), secondary nitrate and secondary organic carbon mixed sources (12.3%) Motor vehicle sources (11.8%) and cement dust sources (7.0%); Analysis of carbon aerosols revealed that the main sources of OC were motor vehicle sources (38.2%), coal-fired biomass combustion mixed sources (33.1%), and secondary organic carbon (25.3%). The main sources of char EC were coal-fired biomass combustion mixed sources and motor vehicle sources, accounting for 50.5% and 45.4%, respectively. Soot EC was mainly affected by motor vehicles (up to 73.2%). Research shows that PM10 in Chengdu mainly comes from crustal dust, secondary generation, and coal-fired biomass combustion, Carbon aerosols mainly come from motor vehicles, coal-fired and biomass combustion
Due to the fact that the atmosphere is a complex medium, the presence of turbulence in the lower atmosphere causes intense exchange of matter and energy, and the diffusion and transmission of pollutants are obvious. It is necessary to conduct three-dimensional observations of the lower atmosphere at different heights and regions to obtain the most direct data on the concentration distribution of gaseous pollutants. It is necessary to comprehensively utilize ground observation stations, tethered balloons, and aircraft platforms, On November 25-26, 2016, a three-dimensional observation was conducted on NOx and O3 under polluted weather conditions in Gaocun, Wuqing, Tianjin. The distribution characteristics of pollutants in the ground, vertical, and low altitude areas were obtained, and analyzed and studied in conjunction with meteorological factors. The observation results showed that the surface level of NOx was relatively high, with a daily average value of 230 × 10-9, exceeding the limit of the second level standard of GB 3095-2012 "Environmental Air Quality Standard", reflects the high pollution level of Gaocun in winter, mainly affected by local traffic source emissions$ Varphi $(NOx) shows a decreasing trend with the increase of altitude, and is significantly affected by wind speed, mainly accumulating below the inversion layer. Low altitude $ varphi $(NOx) in urban areas is higher than that in suburban areas, while in more remote suburban areas, Gaocun $ varphi $(NOx) is equivalent to that in urban areas, which also reflects the high level of NOx pollution in Gaocun. Gaocun's ground $ varphi $(O3) is low, with a daily maximum 8-hour average value of 8 × 10-9 reflects the characteristics of weak low-temperature radiation and low intensity of photochemical reactions in winter. As altitude increases, $ varphi $(O3) shows an upward trend, and the vertical distribution characteristics are mainly related to temperature stratification. Low altitude $ varphi $(O3) shows a higher level in suburban areas than in urban areas, and a higher level in high villages (outer suburbs) than in suburban areas. Research shows that an increase in $ varphi $(NOx) leads to a decrease in $ varphi $(O3), This may be related to the low levels of $ varphi $(VOCs)/$ varphi $(NOx) in winter in Takamura, and further analysis is needed in conjunction with VOCs observation data
In the new era, China's environmental protection situation is facing profound changes, and meeting the growing demand for high-quality ecological products by the people has become the main contradiction in environmental protection work. In order to implement the requirements of the 19th National Congress of the Communist Party of China on ecological civilization construction and environmental protection, firmly grasp the 'people-oriented nature of environmental technology', based on the analysis and judgment of the future environmental situation and the demand for environmental technology innovation, closely revolve around the goals of green development and environmental quality improvement, Four key tasks were proposed to strengthen the innovative development of environmental protection technology: facing the main battlefield of green development of the national economy, comprehensively improving the supply capacity and level of environmental protection technology; Strengthen basic research in environmental science and lead the improvement of environmental quality; Research and develop key technologies to break through the bottleneck of environmental governance technology; Strengthen the protection of ecosystems and promote the harmonious coexistence of humans and nature. At the same time, five suggestions for improving the innovation system and mechanism of environmental protection technology have been proposed: implement platformization, internationalization, industrialization, standardization, and information management, and promote the construction of modern environmental research institutions; Accelerate the construction of the environmental protection technology innovation system, improve and strengthen the technology innovation chain; Improve the management decision-making support mechanism and solve the problem of disconnection between scientific research and management; Coordinate the national environmental research force and innovate the organizational model of major scientific research projects; Strengthen the construction of talent teams, fully mobilize the innovative vitality of talents, and provide policy and institutional guarantees for environmental protection technology innovation
In order to study the pollution characteristics and sources of carbon components in winter atmospheric particulate matter in Heze City, PM2.5 and PM10 samples were collected in January 2016. The content of OC (organic carbon), EC (elemental carbon), and 8 carbon components [OC1, OC2, OC3, OC4, EC1, EC2, EC3, and OP (pyrolysis carbon)] in the samples were analyzed using thermal light reflection method, and the results were calculated ρ (Char-EC) (Char-EC is the EC in the solid residue after fuel combustion) and ρ (Soot EC) (Soot EC is the EC formed by the condensation of volatile substances in the gas phase after combustion), in order to qualitatively identify the source of carbon components in atmospheric particulate matter. The results show that the carbon component concentration in winter atmospheric particulate matter samples in Heze City is at a high level, while in PM2.5 ρ (OC) ρ (EC) 26.34 and 9.22 respectively μ G/m3, in PM10 ρ (OC) ρ (EC) 31.82 and 10.71 respectively μ During the sampling period, the ratio of the concentration of carbon components (OC, EC, OC1, OC2, OC3, OC4, EC1, EC2, EC3, Char-EC, Soot EC) in atmospheric PM2.5 to the concentration of corresponding components in PM10 was greater than 0.5 (0.60-0.90), indicating that carbon components are mostly concentrated in fine particles (PM2.5). There are significant spatial differences in the concentration of carbon components in atmospheric particulate matter samples, and the concentrations of each carbon component in atmospheric PM2.5 and PM10 at each point are significant ρ (OC) are significantly higher than ρ (EC) (T-test, P<0.05). The Char-EC/Soot-EC (mass concentration ratio) in winter atmospheric PM2.5 and PM10 in Heze City are 10.04 and 8.00 respectively, and there is significant spatial difference (T-test, P<0.05). The analysis results of PMF (positive definite matrix factorization method) show that there are four main sources of carbon components in winter atmospheric PM2.5 and PM10 in Heze City, This includes two types of diesel vehicles (EC2 is the main carbon component in Class 1 emissions, defined as diesel vehicle-1; EC3 is the main carbon component in Class 1 emissions, defined as diesel vehicle-2), gasoline vehicles, biomass combustion, and coal-fired hybrid sources, with a contribution rate of 13.98%, 5.13%, 24.47%, 41.97% to the carbon component in atmospheric PM2.5, and 16.08%, 8.21%, 18.34%, and 47.35% to the carbon component in atmospheric PM10, respectively, The main sources of carbon in winter atmospheric PM2.5 and PM10 in Heze City are diesel vehicles, gasoline vehicles, biomass combustion, and coal combustion
To explore the heating season inside and outside urban forests ρ Based on the data from the air quality monitoring station in Xishan National Forest Park and the real-time data from the botanical garden monitoring station of the Beijing Environmental Protection Monitoring Center, the dynamic changes and differences of (SO2) were analyzed for the 2015 heating season in and out of urban forests ρ Changes and influencing factors of (SO2). The results indicate that: inside and outside the forest ρ The daily variation of (SO2) shows a double peak and double valley pattern, reaching its peak around 09:00 to 11:00 and 20:00 to 22:00; Sampling period ρ The monthly variation of (SO2) shows an insignificant 'V' pattern, with the highest value appearing in January. The values inside and outside the forest are (25.8 ± 9.2) and (31.7 ± 23.4), respectively μ G/m3, with the lowest value appearing in November, and the values inside and outside the forest are (19.0 ± 5.2) and (13.0 ± 11.2), respectively μ G/m3. In the forest ρ (SO2) is lower than outside the forest from January to March, higher than outside the forest from November to December, and within the forest ρ The change of SO2 is relatively gentle outside the forest; Meteorological conditions affecting urban forests during the heating season ρ Changes in (SO2) have a significant impact: precipitation has a significant impact on ρ (SO2) has a significant reduction effect, with strong winds having the effect of dispersing SO2 and being influenced by wind direction; ρ The relationship between (SO2) and temperature is not significant (P=0.05, R<0.40), but there is a significant linear relationship with relative humidity of the air（ α= 0.05, Sig=0.00), the impact of meteorological factors inside the forest is lower than that outside the forest. Research has shown that urban forests have a certain buffering, resistance, and absorption capacity for gaseous pollutants. Therefore, attention should be paid to the development of urban forest ecosystems, and their ecological benefits should be fully utilized to improve the quality of urban atmospheric environment
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