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In this cross-sectional study of 1475 Chinese university students, we explored associated factors of attitude and willingness of biodiversity conservation, analyzed the hypothesized mediation by social support in the association between attitude and willingness of biodiversity conservation. Multivariate logistic regression model revealed that major and social support were prominently related to both attitude and willingness of biodiversity conservation. Besides, path model identified a statistically significant mediation by social support, sex, race, and family residence presented noticeable effect modification on the mediation of social support. These major findings suggest that intervention measures which aiming at enhancing social support could be considered for elevating attitude and willingness of biodiversity conservation among Chinese university students. [ABSTRACT FROM AUTHOR]

This study was based on the observation of volatile organic compounds (VOCs), conventional gaseous air pollutants, and meteorological parameters observed at the Xinxiang Municipal Party School site from June to August 2021. The ozone (O 3 ) characteristics and sensitivity of O 3 pollution days and the control strategy of its precursors were studied using an observation-based model (OBM). It was found that the meteorological conditions were characterized by high temperature, low humidity, and low pressure in O 3 -pollution days. The concentrations of O 3 and its precursors all increased in the O 3 pollution days. Oxygenated volatile organic compounds (OVOCs) and alkanes were the highest-concentration components of VOCs on O 3 pollution days in Xinxiang, and OVOCs had the highest ozone formation potential (OFP) and hydroxyl (·OH) reactivity. According to the relative incremental reactivity (RIR) analysis, during the O 3 pollution days in Xinxiang, O 3 sensitivity was in the VOCs-limited regime in June and in the transitional regime in July and August. Ozone production was more sensitive to alkenes and OVOCs. The RIR values of the precursors in June changed throughout the day, but O 3 sensitivity remained the VOCs-limited regime. In July and August, O 3 sensitivity was the VOCs-limited regime in the morning, transitional regime at noon, transitional and NO x -limited regime, respectively in the afternoon. By simulating different precursor-reduction scenarios, the results showed that the reduction of VOCs was always beneficial to the control of O 3 , whereas the reduction of NO x had little effect on the control of O 3 and a risk of increasing O 3 .

In order to better understand the industrial volatile organic compounds(VOCs) emissions in China in recent years, an industrial VOCs emission inventory was developed from 2011 to 2019, based on the dynamic emission factors method and the comprehensive source classification system. The results showed that VOCs emissions increased first from 11122.7 kt in 2011 to 13397.9 kt in 2017, and then decreased to 13247.0 kt in 2019. The emission structure of the four source categories changed. The contribution from basic organic chemical industries, gasoline storage and transportation, manufacturing(i.e., coatings, inks, pigments, and similar products), and industrial protective coatings continued to increase. On the contrary, the contributions of oil and natural gas processing, automobile, and container manufacturing industries declined over the study period. Among the industrial emissions in China in 2019, industrial coating, printing, and basic organic chemical industries emitted large amounts of VOCs(accounting for 39.2% of the total emission), and because their contribution became increasingly prominent since 2011, these sectors will be the key emission sources in the future. With respect to the spatial distribution in 2019, East China and South China had the largest VOCs emissions. Shandong, Guangdong, Jiangsu, and Zhejiang were the four provinces that contributed the most, accounting for 40.6% of the total VOCs emissions.

To determine the differences in emissions among different types of coatings, such as solvent-based, water-based, solvent-based ultra-violet(UV), water-based UV, and powder coatings, representative furniture manufacturing companies were selected for analysis. The emission concentrations and compositional characteristics of volatile organic compounds(VOCs) in different types of coatings were compared and studied. The ozone formation potential(OFP) and secondary organic aerosol formation potential(SOAFP) of the different types of coatings were also analyzed. Solvent-based coatings has higher TVOC concentrations, OFPs, and SOAFPs than water-based, solvent-based UV, water-based UV, and powder coatings. The concentrations and composition of VOCs emitted from the different types of coatings were also different. The main VOC groups of the solvent-based and solvent-based UV coatings were aromatic hydrocarbons and oxygenated volatile organic compounds(OVOCs). Specifically, the proportions of aromatic hydrocarbons are 41.91%-60.67% and 42.51%-43.00%, respectively, and the proportions of OVOCs were 24.75%-41.29% and 41.34%-43.21%, respectively. OVOCs accounted for the highest proportion of VOCs in the water-based, water-based UV, and powder coatings, at 54.02%-62.10%, 55.23%-64.81%, and 42.98%-46.45%, respectively. The major VOC compound of the solvent-based coatings was styrene(14.68%), and the main component of the water-based coatings was methylal(14.61%). The main species of VOCs from the solvent-based UV and water-based UV coatings were butyl acetate(15.36% and 20.56%, respectively). The most abundant species from the powder coatings was ethyl 3-ethoxy propionate(20.19%). Aromatic hydrocarbons were the most important contributor to the OFP of the solvent-based and solvent-based UV coatings, accounting for 79.84% and 80.32%, respectively. Aromatic hydrocarbons(51.48% and 36.71%) and OVOCs(42.30% and 41.03%) were the major contributors to the OFP of the water-based and water-based UV coatings, respectively. Aromatic hydrocarbons(43.46%), OVOCs(28.06%), and olefins(25.24%) were the main factors affecting the OFP of the powder coatings. Aromatic hydrocarbons dominate the SOAFP of solvent-based, water-based, solvent-based UV, water-based UV, and powder coatings, accounting for more than 99%.

Based on the ground-level ozone concentration monitoring data in 2018, the ozone concentrations in 338 cities at the prefecture level and above were analyzed, and the TCEQ method was utilized to calculate the amount of locally generated ozone and regionally transported ozone in each city to divide the national ozone pollution control area and develop appropriate ozone pollution control measures. Correlation analysis was conducted between the amount of locally generated ozone and the daily maximum 8 h average ozone in each city to determine the main source of ozone pollution by determination coefficient ( R 2 ). The results show that 121 cities (35.8%) in China exceeded the standard in O 3 concentration in 2018. The local generation of O 3 in 104 cities has a great impact on the local O 3 pollution, and is its main cause. In the other 234 cities, the main source of O 3 pollution is regionally transported O 3 . Cities are classified into four categories based on their ozone concentration levels and pollution sources:cities with a nonattainment ozone situation and mainly locally generated ozone (N-L), cities with a nonattainment ozone situation and mainly regionally transported ozone (N-T), cities with a standard ozone situation and mainly locally generated ozone (S-L), and cities with a standard ozone situation and mainly regionally transported ozone (S-T). Finally, according to the proportion of four city types in each province, the whole country is divided into three types of control areas:severe, moderate, and general. N-L cities in the severe control area account for the largest proportion (20.3%) of the three types of control areas and the pollution is the highest; the proportion of the four categories of cities in the moderate control area are all medium; the general control area mainly includes S-T cities (65.4%), and the pollution is the lowest.