Spatial Association Pattern of Air Pollution and Influencing Factors in the Beijing-Tianjin-Hebei Air Pollution Transmission Channel: A Case Study in Henan Province

Identification of NOx emissions and source characteristics by TROPOMI observations - A case study in north-central Henan, China

With the development of industries, air pollution in north-central Henan is becoming increasingly severe. The TROPOspheric Monitoring Instrument (TROPOMI) provides nitrogen dioxide (NO2) column densities with high spatial resolution. Based on TROPOMI, in this study, the nitrogen oxides (NOx) emissions in north-central Henan are derived and the emission hotspots are identified with the flux divergence method (FDM) from May to September 2021. The results indicate that Zhengzhou has the highest NOx emissions in north-central Henan. The most prominent hotspots are in Guancheng Huizu District (Zhengzhou) and Yindu District (Anyang), with emissions of 448.4 g/s and 300.3 g/s, respectively. The Gaussian Mixture Model (GMM) is applied to quantify the characteristics of emission hotspots, including the diameter, eccentricity, and tilt angle, among which the tilt angle provides a novel metric for identifying the spatial distribution of pollution sources. Furthermore, the results are compared with the CAMS global anthropogenic emissions (CAMS-GLOB-ANT) and Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC), and they are generally in good agreement. However, some point sources, such as power plants, may be missed by both inventories. It is also found that for emission hotspots near transportation hubs, CAMS-GLOB-ANT may not have fully considered the actual traffic flow, leading to an underestimation of transportation emissions. These findings provide key information for the accurate implementation of pollution prevention and control measures, as well as references for future optimization of emission inventories. Consequently, deriving NOx emissions from space, quantifying the characteristics of emission hotspots, and combining them with bottom-up inventories can provide valuable insights for targeted emission control.

Driving forces and relationship between air pollution and economic growth based on EKC hypothesis and STIRPAT model: evidence from Henan Province, China

The aim of this research is to analyze the main influencing factors and relationship between atmospheric environment and economic society. Using the panel data of 18 cities in Henan Province from 2006 to 2020, this paper employed some advanced econometric estimation included entropy method, extended environmental Kuznets curve (EKC) and STIRPAT model to conduct empirical estimations. The results show that most regions in Henan Province have verified the existence of the EKC hypothesis; and the peak of air pollution level in all cities of Henan Province generally occurred in around 2014. Multiple linear Ridge regression indicated that the positive driving forces of air pollution in most cities in Henan Province are industrial structure and population size; the negative driving forces are urbanization level, technical level and greening degree. Finally, we used the grey GM (1, 1) model to predict the atmospheric environment of Henan Province in 2025, 2030, 2035 and 2040. What should pay close attention to is that air pollution levels in northeastern and central Henan Province will continue to remain high.

Comparison and implications of the carbonaceous fractions under different environments in polluted central plains in China: Insight from the lockdown of COVID-19 outbreak

Before and during the COVID-19 outbreak in the heated winter season of 2019, the carbonaceous fractions including organic carbon (OC), elemental carbon (EC), OC1-4, and EC1-5 were investigated between normal (November 1, 2019, to January 24, 2020) and lockdown (January 25, to February 29, 2020) periods in polluted regions of northern Henan Province. In comparison to urban site, four rural sites showed higher concentrations of carbonaceous components, especially secondary OC (SOC); the concentration of SOC in rural sites was 1.5-3.4 times that in the urban site. During the lockdown period, SOC in urban site decreased slightly, while it increased significantly in rural sites. NO₂ has a significant effect on SOC generation, particularly in normal period when NO₂ concentrations were high. Nevertheless, NO₂ significantly decreased, and the elevated O₃ (increased by 103-138%) contributed considerably to the generation of SOC during lockdown. Relative humidity (RH) promoted SOC production when RH was below 60%, but SOC was negatively correlated or uncorrelated with RH when RH exceeded 60%. Additionally, RH has a more pronounced effect on SOC during lockdown. The contribution of gasoline vehicle emissions decreases significantly in both urban and rural sites (3-12%) due to the significant reduction of anthropogenic activities during lockdown, although the urban site remained with the biggest contributions (37%). These results provide innovative insights into the variations in carbonaceous aerosols and SOC generation during the unique time when anthropogenic sources were significantly reduced and illustrate the differences in pollution characteristics and sources of carbonaceous fractions in different environments.

Analysis on Spatio-Temporal Evolution and Influencing Factors of Air Quality Index (AQI) in China

After the reform and opening up, China's economy has developed rapidly. However, environmental problems have gradually emerged, the top of which is air pollution. We have used the following methods: In view of the shortcomings of the current spatio-temporal evolution analysis of the Air Quality Index (AQI) that is not detailed to the county level and the lack of analysis of its underlying causes, this study collects the AQI of all counties in China from 2014 to 2021, and uses spatial autocorrelation and other analysis methods to deeply analyze the spatio-temporal evolution characteristic. Based on the provincial panel data, the spatial econometric model is used to explore its influencing factors and spillover effects. The research results show that: (1) From 2014 to 2021, the AQI of all counties in China showed obvious spatial agglomeration characteristics, and counties in central and western Xinjiang, as well as Beijing, Tianjin, and Hebei, were high-value agglomeration areas; (2) the change trend of the AQI value also has obvious spatial autocorrelation, and generally presents a downward trend. However, the AQI value in a small number of regions, such as Xinjiang, shows a slow decline or even a reverse rise; (3) there are some of the main factors affecting AQI, such as GDP per capita, percentage of forest cover, total emissions of SO₂, and these factors have different impacts on different regions. In addition, the increase of GDP per capita, the reduction of industrialization level, and the increase of forest coverage will significantly improve the air quality of other surrounding provinces. An in-depth analysis of the spatio-temporal evolution, influencing factors, and spillover effects of AQI in China is conducive to formulating countermeasures to improve air quality according to local conditions and promoting regional sustainable development.

Air pollution and innovation performance of Chinese cities: human capital and labour cost perspective

Environmental protection and innovation performance are key issues that affect the sustainable development and value growth of cities. Using data of 272 prefecture-level cities during 2002-2016 and 2,169 listed companies, and the air ventilation coefficient and government environmental regulations, as the instrumental variables for PM_2.5 concentrations, this paper applies two-stage OLS (2SLS) to investigate how air pollution affects China's technological innovation and its realization mechanism. The results indicate that the rise in air pollution significantly inhibits the technological innovation level of regions as a whole as well as individual enterprises. When considering the spatial effect of the spread of PM_2.5 concentrations, due to positive spillover effects on innovation activities, the spread of air pollution has negative impacts on technological innovation activities in surrounding cities. Human capital and labour costs are important channels through which air pollution influences China's technological innovation. The implementation of pilot carbon trading policies can effectively reduce air pollution and then contribute to the achievement of the goals of the green growth strategy.

Short-term effects of indoor and outdoor air pollution on the lung cancer morbidity in Henan Province, Central China

Lung cancer is one of the most common cancer types and a major cause of death. The relationship between lung cancer morbidity and exposure to air pollutants is of particular concern. However, the relationship and difference in lung cancer morbidity between indoor and outdoor air pollution effects remain unclear. In this paper, the aim was to comprehensively investigate the spatial relationships between the lung cancer morbidity and indoor-outdoor air pollution in Henan based on the standard deviation ellipse, spatial autocorrelation analysis and GeoDetector. The results indicated that (1) the spatial distribution of lung cancer morbidity was related to the geomorphology, while high-morbidity areas were concentrated in the plains and basins of Central, Eastern and Southern Henan. (2) Among the selected outdoor air pollutants, PM_2.5, NO₂, SO₂, O₃ and CO were significantly correlated with the lung cancer morbidity. The degree of indoor air pollution was measured by the use of heating energy, and the proportions of coal-heating households, households with coal/biomass stoves and households with heated kangs were highly decisive in regard to the lung cancer morbidity. (3) The interaction between two factors was more notable than a single factor in explaining the lung cancer morbidity. Moreover, the interaction type was mainly nonlinear enhancement, and the proportion of households with coal/biomass stoves imposed the strongest interaction effect on the other factors.

Ventilation Capacities of Chinese Industrial Cities and Their Influence on the Concentration of NO2

Most cities in China, especially industrial cities, are facing severe air pollution, which affects the health of the residents and the development of cities. One of the most effective ways to alleviate air pollution is to improve the urban ventilation environment; however, few studies have focused on the relationship between them. The Frontal Area Index (FAI) can reflect the obstructive effect of buildings on wind. It is influenced by urban architectural form and is an attribute of the city itself that can be used to accurately measure the ventilation capacity or ventilation potential of the city. Here, the FAIs of 45 industrial cities of different sizes in different climatic zones in China were computed, and the relationship between the FAI and the concentration of typical pollutants, i.e., NO2, were analyzed. It was found that (1) the FAIs of most of the industrial cities in China were less than 0.45, indicating that most of the industrial cities in China have excellent and good ventilation capacities; (2) there were significant differences in the ventilation capacities of different cities, and the ventilation capacity decreased from the temperate to the tropical climate zone and increased from large to small cities; (3) there was a significant difference in the ventilation capacity in winter and summer, indicating that that with the exception of building height and building density, wind direction was also the main influencing factor of FAI; (4) the concentration of NO2 was significantly correlated with the FAI, and the relative contribution of the FAI to the NO2 concentration was stable at approximately 9% and was generally higher than other socioeconomic factors. There was a turning point in the influence of the FAI on the NO2 concentration (0.18 < FAI < 0.49), below which the FAI had a strong influence on the NO2 concentration, and above which the influence of the FAI became weaker. The results of this study can provide guidance for suppressing urban air pollution through urban planning.

Air pollution increased risk of reproductive system diseases: a 5-year outcome analysis of different pollutants in different seasons, ages, and genders

Air pollution remains a serious environmental problem worldwide, and the effects of air pollutants with reproductive system diseases have already attracted extensive attention. The present study investigated the risk of air pollutants on reproductive system diseases, based on daily medical visits (DMV) of the past 5 years in central China. Data of DMV outpatients with reproductive system diseases were obtained from a general hospital in Zhengzhou, October 28, 2013 to May 31, 2018, as well as atmospheric pollutants data. Correlation of air pollutants and DMV was analyzed with distributed lag nonlinear model (DLNM), including total cases of reproductive system diseases, and in different seasons (spring, summer, autumn, and winter), genders (male and female), and age groups (<26, 26-35, and >35 years old). A total of 374,558 visits were included. NO2 was most closely relevant to incidence risk of total cases analysis with each increased interquartile ranges (IQRs) in the 6 pollutants, with 30-day lag. Relationship to pollutants was more sensitive in fall, >35 years old, and male groups than in other seasons, ages, and females, and NO2 had the highest risk on reproductive diseases. Air pollution increased risk of reproductive system diseases, and different pollutants played different roles in different seasons, ages, and genders. The results of this study will provide evidence for effective air quality controlling and human reproductive protection.

Environmental effects of prohibiting urban fireworks and firecrackers in Jinan, China

Eight national air quality monitoring stations were selected to examine the environmental effects of prohibiting fireworks and firecrackers since January 1, 2018, in Jinan, China, by using an air quality index (AQI) on three time scales. In 2014-2018, the average annual AQI decreased year on year, but a downward trend in 2018 was only found by applying a Daniel trend test. The change in monthly data for 2016-2018 followed a "W" pattern. The overall AQI value was lower on New Year's Eve than during Spring Festival, and the 2-day AQI in 2018 was lower than that in 2017. The GIS analysis method was used for spatial visualization. The AQI in the built-up part of Jinan was high in the west and low in the east on New Year's Eve and Spring Festival of 2017, being lowest in the Development Zone. The AQI spatial distribution was high in the city core but low in its periphery; in 2018, the high-AQI center appeared near the Provincial Seed Warehouse on New Year's Eve and Spring Festival. Multiple linear regression was used to analyze the relationship between AQI and pollutants. Six pollutants were found to be positively correlated with the AQI. PM_2.5 and PM₁₀ had the strongest correlations on New Year's Eve and Spring Festival, for which the correlations of SO₂, CO, and NO₂ were significantly weaker in 2018 than in 2017.