Refined assessment and decomposition analysis of carbon emissions in high-energy intensive industrial sectors in China.

Carbon emissions from high-energy intensive industrial sectors are the focus of this study due to the huge energy consumption of these sectors. A refined carbon emission inventory of Chinese high-energy intensive industrial sectors in 2020 was first developed at the point source level. The results showed that coal-fired power plants (CFPPs) were the leading contributors to carbon emissions, followed by iron and steel smelting (ISS) and cement production (CMP). Provinces with high carbon emission intensity were mainly concentrated in the north and northeast coasts, while exhibiting a developed economic level and a concentration of heavy industries. Additionally, the growth in China's industrial carbon emissions from 1995 to 2020 can be divided into three phases. The largest decrease in emission intensity was observed in Central, Southwest, North, and East China. Furthermore, the economic structure remained the dominant driver of carbon emissions from the 10th to 13th Five-Year Plan (FYP), playing a positive promotional role. The contribution of economic structure, energy intensity, and energy structure to carbon emissions varied substantially by region and period. With the proposal of sustainable development and energy conservation in China, the influence of economic structure on the carbon emissions of industrial sectors has gradually weakened since the 11th FYP. The reduction in industrial carbon emissions in China under three scenarios could reach up to 46.6 % from 2030 to 2050. The results indicate that industrial carbon emission control in China needs to be integrated into the refined control pathway for conventional air pollutants, considering the spatial variability of industrial carbon emissions in China.

Application of loofah and insects in a bio-trickling filter to relieve clogging.

Bio-trickling filters (BTFs) use an inert filler to purify pollutants making them prone to clogging due to bacterial accumulation. To investigate the performance of a non-inert filler in BTF and its cooperation with insects to relieve clogging, a vertical BTF was constructed with a loofah/Pall ring/polydimethylsiloxane composite filler and selected bacteria to purify toluene. The BTF was started up within 17 d and restarted within 3 d after starvation for 12-16 d. Its average removal efficiency was >90% at steady state. The maximum elimination capacity of 86.4 g·(m3·h)-1 was obtained at a volume capacity of 96.2 g·(m3·h)-1. The introduction of holometabolous insects (Clogmia albipunctata) rapidly removed the biofilm and accelerated the degradation of the loofah, which alleviated clogging. Furthermore, confocal laser scanning microscope (CLSM) observations showed that the biofilm polysaccharides were difficult to remove, while lipids were readily lost. Analysis of microbial diversity over time and space revealed that the dominant bacterium, Comamonas, was replaced by diverse microflora with no obvious dominant genus. Insect introduction and loofah migration had little effect on the evolution of microflora. This study provides a promising approach to operating BTFs with less clogging.

Identification of NOx hotspots from oversampled TROPOMI NO2 column based on image segmentation method.

Satellite-based measures of NO2 have become increasingly available for resolving the limitation on insufficient spatial and temporal coverage of ground-level monitoring networks. Oversampled NO2 column density can obtain more detailed features of NO2 column with a spatial resolution as high as 2 km × 2 km, while it is still challenging to identify hotspots of NOx pollution plume in city-scale due to background interference. In this study, we proposed a method for detecting the NOx hotspot grids from oversampled satellite NO2 column based on the image segmentation method, and identifying major source types using Term frequency-inverse document frequency (TF-IDF). A fractal model was used to evaluate and eliminate the background portion of the NO2 column and an adaptive threshold method was adopted to identify the region of interest (ROI) of local hotspot NO2 column. Hot-grid index, counting the frequency of NO2 hotspot ROI in each grid, was conducted to identify the hotspot grids. TF-IDF was used to semantically analyze the major source types of NO2 hotspot grids. Taking Central and Eastern China as the studied domain, the hotspot grids of NO2 and the relevant major source types were identified based on the proposed method. The major non-road mobile sources (such as Beijing Capital International Airport), industrial areas (such as Caofeidian Industrial Park) and urban areas were clearly distinguished. The power plant, Coke and Iron and Steel were identified as major source types in the whole year in the corresponding NOx hotspot grids. Notably, the identification of hotspot grids indicated a higher probability of a local high-intensity NOx pollution plume rather than a quantitative NOx emission; the key source types were the semantic keywords in hotspot grids, which does not mean there were no other exiting emission sources. This proposed method has strong implications on rapidly identifying the NOx hotspot grids based on oversampled TROPOMI NO2 column and the list of industrial enterprises.

Measure-specific environmental benefits of air pollution control for coal-fired industrial boilers in China from 2015 to 2017.

From 2015 to 2017, China took strong air pollution control measures (APCMs) for coal-fired industrial boilers (CFIBs), including eliminating CFIBs, promoting clean fuels, and updating air pollution control devices (APCDs). Based on the industrial boiler's emission inventory of air pollutants, measure-specific emission reductions from 2015 to 2017 was estimated in this study. Besides, the measure-specific environmental benefits of unit emission reduction on concentration and deposition flux were systematically evaluated by WRF-CMAQ model. The total emission reductions for CFIBs of PM10, PM2.5, SO2, NOx, Hg, As, Cd, Cr and Pb from 2015 to 2017 were 1.2 Tg, 0.53 Tg, 2.06 Tg, 0.65 Tg, 37.6 tons, 179.5 tons, 17.9 tons, 1029.3 tons and 676.0 tons, respectively. Based on meteorological fields in 2017, their corresponding national population-weighted mitigated concentration was 1.8 µg m-3, 1.3 µg m-3, 3.6 µg m-3, 0.6 µg m-3 (NO2), 0.076 ng m-3, 0.37 ng m-3, 0.04 ng m-3, 1.83 ng m-3 and 2.3 ng m-3, respectively. Updating APCDs was identified as the major measure to reduce air pollutants (except NOx), accounting for more than 35% of emission reductions and mitigated concentration. Moreover, elimination was the major NOx reduction method, contributing to 55% of NOx emission reductions. The promoting of fuels, including replacement of CFIBs with gas-fired and biomass-fired industrial boilers, had higher environmental benefits for unit emission reductions. Furthermore, there were still more than 43,000 CFIBs with the capacity <10 t h-1, accounting for 14%, 21%, and 11% of total PM2.5, SO2, and NOX emissions for CFIBs in 2017; meanwhile, 20% and 59% of CFIBs did not install flue gas desulfurization and denitrification devices, respectively. Therefore, it is recommended to give priority to phase out CFIBs with capacity <10 t h-1 and APCDs updating for larger capacity CFIBs in the future.

Refined spatio-temporal emission assessment of Hg, As, Cd, Cr and Pb from Chinese coal-fired industrial boilers.

Coal-fired industrial boilers (CFIBs) are a significant source of trace metals (TMs) emissions, due to its large number and widespread industry application. In this study, a highly resolved of county-based atmospheric emission inventory of Hg, As, Cd, Cr and Pb for Chinese CFIBs in 2017 is established firstly based on integrated source-specific information of both activity level and air pollution control devices (APCDs) from ~61,000 CFIBs in mainland China. Our results estimated that the total emissions of Hg, As, Cd, Cr and Pb from national CFIBs in 2017 were about 25.46, 115.33, 7.04, 371.40, and 589.76 t, respectively. Hg0 was the majority species of atmospheric Hg, accounting for 71.5% of the total Hg emission. The peak emission intensities of five TMs were mainly concentrated in northern and eastern region of China due to its large demand of coal consumption for winter heating, broad economic activity, as well as high population density. Monthly emission characteristics of TMs exhibited seasonal peak. The overall uncertainties of the newly updated emission inventory were estimated at the ranges of -42.0%-45.5%. Generally, TMs emissions from Chinese CFIBs were effectively controlled through implementing energy substitution, APCDs upgrading, and ultra-low emission (ULE) retrofitting in different regions of China, which contributed to 18.8%-29.4% of five TMs emission reductions. We believe that our highly resolved county-level emission inventory will be comprehensively explored the current tempo-spatial emission characteristics of atmospheric TMs from Chinese CFIBs and the forecast results will be useful for developing effective emission control programs for policy makers in the county levels and improving the regional air quality in the future.