Beijing‐Tianjin‐Hebei area is one of the most polluted areas in China. This paper used the Fifth‐Generation Penn State/NCAR Mesoscale Model (MM5) and Model‐3/Community Multiscale Air Quality (CMAQ) modeling system to quantify the source contribution to PM_2.5 in Hebei cities in order to obtain an in‐depth understanding haze process in January and February 2013, using the Multiresolution Emission Inventory for China (MEIC). The result showed that PM_2.5 were mainly originated from the southern Hebei (SHB) with the fractions of 70.8% and 66.4% to Shijiazhuang, 70.6% and 63.9% to Xingtai, and 68.5% and 63.0% to Handan in January and February 2013, respectively. The northern Hebei (NHB) contributed 69.8% and 70.7% to Zhangjiakou, 68.7% and 66.2% to Chengde, and 57.7% and 59.6% to Qinhuangdao in January and February. In Cangzhou, Hengshui, and Langfang, regional joint policy making should be implemented due to the pollution of multiple sources. In Baoding and Tangshan, industrial emissions contributed 38.1% and 41.9% of PM_2.5 to Baoding and 39.8% and 45.8% to Tangshan in January and February, respectively. Industrial and domestic emissions should be controlled in Tangshan and Baoding, especially for industrial emissions of NHB.

A reduction in gaseous pollutants is an important method for mitigating PM_2.5 concentration in the atmosphere, and the reduction in SO₂/NH₃/NO_x is beneficial to control secondary inorganic aerosols in PM_2.5. In this study, the Weather Research and Forecasting model with Chemistry model (WRF-Chem) was applied to study the impact on the PM_2.5 and its secondary inorganic aerosols using the scenario simulation method in the Beijing–Tianjin–Hebei (BTH) region. The results showed that the BTH region is characterized by being NH₃-rich and having a higher [NH₄⁺]/[SO₄²⁻] ratio in southern BTH, with a ratio of more than 6.0. Source contribution to PM_2.5 was highest in the 30%_SO₂_40%_NH₃_40%_NO_x scenario, with a contribution ratio of 6.8%, followed by 3.8% contribution in the 30%_SO₂_40%_NH₃ scenario, and a 3.4% contribution in the 30%_SO₂_60%_NH₃_60%_NO_x scenario. These results indicate that synergistic reduction measures may be suitable for controlling PM_2.5 concentrations. A lower sensitivity factor, β value between PM_2.5 and NH₃ suggests that solely reducing NH₃ emissions is not beneficial for the BTH region. However, this study indicates that the sensitivity of NO₃⁻ would improve significantly if NH₃ emissions are reduced sharply. A slight reduction in NH₃ was found to be beneficial for controlling NO₃⁻ in medium and small cities, while a significant decrease in NH₃ would be more suitable for mega-cities. The study also observed that SO₄²⁻ and its constituents continued to decrease with a consistent β value of approximately 0.14 in the 30%_SO₂_%_NH₃ scenario and between 10.5 and 12.8 in the 30%_SO₂_%_NH₃_%_NO_x scenario. These findings suggest that a synergistic reduction in SO₂-NH₃-NO_x emissions may be more effective in reducing PM_2.5 concentrations and its secondary inorganic aerosols (SIAs). However, it is important to ensure that the reduction in NH₃ and NO_x exceeds 60% in low SO₂ concentration conditions.

Tea (Camellia sinensis L.) has became one of the most consumed beverages in the world in the past five thousand years, and tea polyphenols (TPs) are important organic acids widely used in chemical, pharmaceutical, food and other industries, which have been shown to exhibit various biological and pharmacological properties. In order to look for new technology of downstream process for TPs separation from green tea waste, selective extraction of TPs with 12 varieties of solvents were carried out, the distribution coefficient and equilibrium experiments at various temperatures were described by extraction isotherms model. The results indicated that the optimum solvent conditions were as follow: extractent was glyceryl triacetate, extraction temperature range was 20~30°C, pH value of crude TPs and reextractant were 3.17 and 9, respectively. Equilibrium data of TPs were successfully fitted to Henry isotherm, the distribution coefficient decreases with the increasing of the temperature, which showing an exothermic adsorption process. The data obtained is useful in the designing of solvent extraction process for the recovery of TPs from green tea waste.

Atmospheric compound pollution is an important challenge in China, with the nonlinear interaction between PM2.5 and O3 presenting a complex pattern of mutual offset and synergistic pollution. This study focused on Puyang, a typical oil and gas industrial city in North China (one of the “2+26” cities), to explore long-term trends and nonlinear interactions of PM_2.5 and O₃ based on monitoring data from 2015 to 2025. PM_2.5 decreased from 79.6 μg·m⁻³ in 2015 to 39.3 μg·m⁻³ in 2025, while MdA8 O₃ increased from 123.0 μg·m⁻³ to 189.6 μg·m⁻³. A weak positive correlation between PM_2.5 and O₃ has been observed when MdA8 O₃ was greater than 160 μg·m⁻³ and PM2.5 was less than 35 μg·m⁻³. The correlation coefficient was 0.38 in winter, 0.37 in summer, 0.26 in autumn, and 0.21 in spring, respectively. O₃ production efficiency (OPE) showed a declining trend and was positively correlated with PM_2.5 (R = 0.46-0.65), with monthly averages consistently above 7, indicating that O₃ was primarily controlled by NOx in this city. This study proposed a seasonal VOCs-NOx control strategy targeting summer photochemical O₃ and autumn–winter dual-exceedance to mitigate PM_2.5, optimize OPE, and reduce exceedance days.

Fine particulate matter (PM_2.5) and ozone (O₃) are the two dominant air pollutants in China, yet their coupling relationship at the daily urban scale remains debated because observational correlations are often confounded by meteorology. This study investigates the nonlinear PM_2.5–O₃ relationship in Puyang, a typical oil and gas industrial city in the “2 + 26” region, using daily observations from 2015 to 2025. A set of progressively nested generalized additive models were constructed, adding meteorological factors and NO₂ sequentially, followed by humidity and season interaction terms. Stratified correlation analyses revealed a concentration-stratified reversal: positive in the low-concentration segment (75 μg·m⁻³; r = −0.313) segments. After controlling for meteorology and NO₂, however, the conditional partial effect increased over most of the PM_2.5 range, indicating that the uncontrolled negative correlation largely disappeared after controlling for meteorology. Humidity exerted a significant conditional modulating effect (p < 0.001), whereas seasonal modulation was concentrated in autumn (p < 0.001). The positive correlation in the low-concentration segment showed a suggestive increase over time (0.190 to 0.306), while the negative correlation in the high-concentration segment weakened (−0.380 to −0.198), indicating an asymmetric redistribution of the PM_2.5–MDA8 O₃ coupling during the clean-air transition. These findings suggest that coordinated control of PM_2.5 and MDA8 O₃ should be designed by concentration interval rather than as a single-direction linear reduction, with precursor-ratio regulation needed in the low-concentration range.