Highly-resolved spatial-temporal variations of air pollutants from Chinese industrial boilers

A novel framework for quantitative attribution of particulate matter pollution mitigation to natural and socioeconomic drivers

Quantifying drivers contributing to air quality improvements is crucial for pollution prevention and optimizing local policies. Despite advances in machine learning for air quality analysis, their limited interpretability hinders attribution on global and local scales, vital for informed city management. Our study introduces an innovative framework quantifying socioeconomic and natural impacts on mitigation of particulate matter pollution in 31 Chinese major cities from 2014 to 2021. Two indices, formulated based on the additivity of Shapley additive explanations, are proposed to measure driver contributions globally and locally. Our analysis explores the self-contained and interactive effects of these drivers on particulate levels, pinpointing critical threshold values where these drivers trigger shifts in particulate matter levels. It is revealed that SO2, NOx, and dust emission reductions collectively account for 51.58 % and 51.96 % of PM2.5 and PM10 decreases at the global level. Moreover, our findings unveil a significant heterogeneity in driver contributions to pollutant mitigation across distinct cities, which can be instrumental in crafting location-specific policy recommendations.

High-precision spatio-temporal variations and future perspectives of multiple air pollutant emissions from Chinese biomass-fired industrial boilers

Biomass-fired industrial boilers (BFIBs) are one of the neglected and important anthropogenic sources of air pollutants. A comprehensive boiler-based emission inventory of multiple air pollutants from BFIBs in China in 2020 was first developed based on the activity level database and updated emission factors. Results showed that national emissions of air pollutants from BFIBs in 2020 were estimated to be 11.5 kt of PM, 10.8 kt of PM10, 7.4 kt of PM2.5, 40.5 kt of SO2, 79.8 kt of NOx, 4.2 kt of organic carbon (OC), 1.0 kt of elemental carbon (EC), 31.7 kt of nonmethane volatile organic compounds (NMVOCs), 15.9 kt of NH3, and 116.5 t of five trace metals (Hg, Cr, Cd, Pb, and As), respectively. Air pollutant emissions exhibited significant spatio-temporal heterogeneity. Monthly air pollutant emissions varied by geographical division due to the combined effects of industrial production and winter heating demand. These emissions were mainly concentrated in the eastern coastal region, with Guangdong, Guangxi, Fujian, Jiangsu, and Zhejiang being the five provinces having the highest emissions. In addition, scenario predictions indicate that as the pollution and carbon reduction strategy is implemented, air pollutant emissions from BFIBs in China could become well controlled, with PM, NOx, SO2, and Hg emissions in 2050 projected to be 3.0-8.3 kt, 36.5-75.7 kt, 16.2-32.8 kt, and 0.52-0.87 t, respectively. Our results can provide a highly spatio-temporal resolution inventory of multiple air pollutant emissions from BFIBs for air quality modelling and support the formulation of air pollution control policies for biomass fuel utilization in the context of the pollution and carbon reduction strategy.

Improved Anthropogenic Mercury Emission Inventories for China from 1980 to 2020: Toward More Accurate Effectiveness Evaluation for the Minamata Convention

Anthropogenic mercury (Hg) emission inventories are crucial for the effectiveness evaluation of the Minamata Convention on Mercury. In this study, we developed an integrated Dynamic Inventory for Mercury Emission (DIME) model and improved the accuracy of emission estimates for primary sources in China. Long-term historical speciated Hg emission inventories for China were established. The total Hg emissions increased from 217.0 t in 1980 to 357.8 t in 2020 with a peak value of 506.6 t in 2010. Three stages with distinct leading drivers were identified. At Stage 1 (1980-1997), Hg emissions doubled with the rapid growth of economy; the driver was offset by the increase of dust and SO₂ control measures at Stage 2 (1997-2010) except for cement production; and co-benefits from strict control measures induced the decoupling of Hg emissions from the economy at Stage 3 (2010-2020). The ultralow emission (ULE) retrofits in key industries had pronounced Hg removal efficiencies. Large emission reduction potential still exists in the cement industry. The improved emission estimation methods for key sectors, the consistency in methodology for historical Hg emission inventories, and the more accurate spatial distribution of speciated Hg emissions in this study provide a practical toolkit for the effectiveness evaluation of the Minamata Convention.

Reaction Behavior and Influencing Mechanisms of Different Fly Ashes on the NO Removal by Using the Ultraviolet Irradiating Chlorite Method

Our previous work had demonstrated that UV/NaClO₂ was the best advanced oxidation method in terms of nitric oxide (NO) removal, but we have not studied the impact of the fly ash on NO removal under such conditions. For this, this paper selected six kinds of fly ashes and studied their effects on NO removal. The micromorphology, elemental composition, and the elemental oxidation states of these six fly ashes were characterized by scanning electron microscopy-energy-dispersive X-ray spectra, X-ray photoelectron spectroscopy, and inductively coupled plasma methods. The main inorganic components in the six fly ashes are metal oxides (Fe₂O₃/Fe₃O₄, SiO₂, Al₂O₃, ZnO, MgO, and TiO₂), carbonates (Na₂CO₃ and CaCO₃), and chlorides (NaCl, KCl, and MgCl₂). The experimental results suggested that high solubility was the premise condition for the fly ashes exhibiting an inhibitory effect on NO removal. Among all of the metal compounds, Fe₂O₃/Fe₃O₄ exhibited the highest inhibitory contribution rate to the NO removal (22.9-45.7%). The anions of Cl^- and CO₃ ^2- acted as scavengers for the free radicals which greatly impaired the oxidation of NO. Based on the simulation experimental results and the UV-vis analysis, the order of inhibitory contribution rates of various metal compounds to the NO removal was determined as Fe₂O₃/Fe₃O₄ > TiO₂ ≈ Na₂CO₃ > Al₂O₃ ≈ ZnO ≈ MnO₂ > CaCO₃ > NaCl > KCl ≈ SiO₂ ≈ MgCl₂.