Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (Max-DOAS) measurements of nitrogen dioxide (NO₂) were continuously obtained from January to November 2019 in northeastern China (NEC). Seasonal variations in the mean NO₂ vertical column densities (VCDs) were apparent, with a maximum of 2.9 × 10¹⁶ molecules cm⁻² in the winter due to enhanced NO₂ emissions from coal-fired winter heating, a longer photochemical lifetime and atmospheric transport. Daily maximum and minimum NO₂ VCDs were observed, independent of the season, at around 11:00 and 13:00 local time, respectively, and the most obvious increases and decreases occurred in the winter and autumn, respectively. The mean diurnal NO₂ VCDs at 11:00 increased to at 08:00 by 1.6, 5.8, and 6.7 × 10¹⁵ molecules cm⁻² in the summer, autumn and winter, respectively, due to increased NO₂ emissions, and then decreased by 2.8, 4.2, and 5.1 × 10¹⁵ molecules cm⁻² at 13:00 in the spring, summer, and autumn, respectively. This was due to strong solar radiation and increased planetary boundary layer height. There was no obvious weekend effect, and the NO₂ VCDs only decreased by about 10% on the weekends. We evaluated the contributions of emissions and transport in the different seasons to the NO₂ VCDs using a generalized additive model, where the contributions of local emissions to the total in the spring, summer, autumn, and winter were 89 ± 12%, 92 ± 11%, 86 ± 12%, and 72 ± 16%, respectively. The contribution of regional transport reached 26% in the winter, and this high contribution value was mainly correlated with the northeast wind, which was due to the transport channel of air pollutants along the Changbai Mountains in NEC. The NO₂/SO₂ ratio was used to identify NO₂ from industrial sources and vehicle exhaust. The contribution of industrial NO₂ VCD sources was >66.3 ± 16% in Shenyang due to the large amount of coal combustion from heavy industrial activity, which emitted large amounts of NO₂. Our results suggest that air quality management in Shenyang should consider reductions in local NO₂ emissions from industrial sources along with regional cooperative control.

The most prominent source of Cu contamination in soils is metal mining and processing, partly since the Middle Age. However, coal mining and combustion can also cause (some) Cu contamination. We studied the distribution of Cu concentrations and isotope ratios in soils of the Huaibei coal mining area. The contribution of the coal mining and combustion to total Cu concentrations in soil was determined with a two-end-member mixing model based on the distinct δ⁶⁵Cu values of the Cu emitted from coal mining and combustion and in native soil. The mean Cu concentration of 75 mg kg⁻¹ exceeded the local soil background value (round to 22.13 mg kg⁻¹). The similar δ⁶⁵Cu value of grass near the coal mining and combustion operation as in gangue and flying ash indicated a superficial Cu contamination. Mining input was the dominant source of Cu in the contaminated soils, contributing up to 95% and on average 72% of the total Cu in the topsoils. The mining-derived Cu was leached to a depth of 65 cm, where still 29% of the Cu could be attributed to the mining emissions. Grasses showed lower δ⁶⁵Cu values than the topsoils, because of the preferential uptake of light Cu isotopes. However, the Δ⁶⁵Cugᵣₐₛₛ₋ₛₒᵢₗ was lower in the contaminated than the uncontaminated area because of superficial adsorption of isotopically heavy Cu from the mining emissions. Overall, in this study the distinct δ⁶⁵Cu values of the mining-derived Cu emissions and the native soil allowed for the quantification of the mining-derived Cu and had already reached the subsoil and contaminated the grass by superficial adsorption in only 60 years of mining operation.

Soil polycyclic aromatic hydrocarbons (PAHs) generated from industrial processes are highly spatially heterologous, with limited quantitative studies on their main influencing factors. The present study evaluated the soil PAHs in three types of industrial parks (a petrochemical industrial park, a brominated flame retardant manufacturing park, and an e-waste dismantling park) and their surroundings. The total concentrations of 16 PAHs in the parks were 340–2.43 × 10³, 26.2–2.63 × 10³, and 394–2.01 × 10⁴ ng/g, which were significantly higher than those in the surrounding areas by 1–2 orders of magnitude, respectively. The highest soil PAH contamination was observed in the e-waste dismantling park. Nap can be considered as characteristic pollutant in the petrochemical industrial park, while Phe in the flame retardant manufacturing park and e-waste dismantling park. Low molecular weight PAHs (2–3 rings) predominated in the petrochemical industrial park (73.0%) and the surrounding area of brominated flame retardant manufacturing park (80.3%). However, high molecular weight PAHs (4–6 rings) were enriched in the other sampling sites, indicating distinct sources and determinants of soil PAHs. Source apportionment results suggested that PAHs in the parks were mainly derived from the leakage of petroleum products in the petroleum manufacturing process and pyrolysis or combustion of fossil fuels. Contrarily, the PAHs in the surrounding areas could have been derived from the historical coal combustion and traffic emissions. Source emissions, wind direction, and local topography influenced the PAH spatial distributions.

The Yellow River Delta (YRD) wetland, the most important estuary wetland in eastern China, has an important ecosystem service function. Rapid and intensive development has inevitably led to the accumulation of potentially toxic elements (PTEs) in soils. Therefore, identifying quantitative sources and spatial distributions of PTEs is essential for soil environmental protection in the YRD. A total of 240 topsoil samples (0–20 cm) were collected in the Yellow River Delta Nature Reserve (YRDNR) and analyzed the PTE contents. To avoid the biases of the single receptor model, positive matrix factorization, factor analysis with nonnegative constraints, and maximum likelihood principal component analysis-multivariate curve resolution-alternating least squares were used for source apportionment of soil PTEs. To promote the efficiency of multivariate geostatistical simulation, a minimum/maximum autocorrelation factor-sequential Gaussian simulation was built to map the spatial patterns of PTEs. Three factors were derived by the three receptor models, and their contributions to the source explanation were similar. As, Cr, Cu, Mn, Ni, and Zn originated from natural sources, with contributions of 85.6%–96.4 %. A total of 61.5 % of Hg was associated with atmospheric deposition of coal combustion and wastewater from upstream. Agricultural activities and oil exploitation contributed 33.5 % and 15.9 % of the Cd and Pb concentrations. Spatial distributions of soil PTEs were controlled by sedimentary grain size. A total of 47.2 % of the total study area was identified as hazardous area for Cd, 10.3 % for As, and 5.4 % for Hg. This work is expected to provide references for soil pollution assessment and management of YRDNR.

Incomplete combustion of solid fuels (animal dung and bituminous coal) is a common phenomenon during residential cooking and heating in the Qinghai-Tibetan Plateau (QTP), resulting in large amounts of pollutants emitted into the atmosphere. This study investigated the pollutant emissions from six burning scenarios (heating and cooking with each of the three different fuels: yak dung, sheep dung, and bitumite) in the QTP's pastoral dwellings. Target pollutants such as carbon monoxide (CO), gas-phase polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), fine particles (PM₂.₅, particulate matter with an aerodynamic diameter < 2.5 μm), carbonaceous aerosols, water-soluble ions, and particle-phase PAHs were investigated. Emission factors (EFs) (mean ± standard deviation) of PM₂.₅ from the six scenarios were in the range of 1.21 ± 0.47–7.03 ± 1.95 g kg⁻¹, of which over 60% mass fractions were carbonaceous aerosols. The ratio of organic carbon to elemental carbon ranged from 9.6 ± 2.7–33.4 ± 11.5 and 81.7 ± 30.4–91.9 ± 29.0 for dung and bitumite burning, respectively. These values were much larger than those reported in the literature, likely because of the region's high altitudes—where the oxygen level is approximately 65% of that at the sea level—thus providing a deficient air supply to stoves. However, the toxicity and carcinogenicity of PAHs emitted from solid fuel combustion in the QTP are significant, despite a slightly lower benzo(a)pyrene-equivalent carcinogenic potency (Bapₑq) in this study than in the literature. The gas-to-particle partitioning coefficient of PAHs and VOC emission profiles in the QTP differed significantly from those reported for other regions in the literature. More attention should be paid to the emissions of PAH derivatives (oxygenated PAHs and nitro-PAHs), considering their enhanced light-absorbing ability and high BaPₑq from solid fuel combustion in the QTP.

This research determines the intertemporal relationships caused by the coal, oil, and natural gas consumption in the carbon dioxide emission by the G7 countries from 1965 to 2018. Auto-regressive and Distributed Lags models and Bound test were used to detect cointegration and understand the dynamic effect. Due to structural breaks occurred in the variables, two dummy variables for the periods of breaks, 1978 and 1990 were incorporated respectively. Positive causality was identified, in the sense that the consumption of fossil fuels provides an increase in carbon dioxide emissions. Short-term elasticities indicate that an increase of 1 percentage point in the consumption of oil, coal, and natural gas will cause, respectively, an increase of 0.4823%, 0.3140%, and 0.1717% in carbon dioxide emissions. In the long run, the increase of 1 percentage point in the consumption of oil, coal, and natural gas will cause, respectively, an increase of 0.4924%, 0.2692%, and 0.1829% in carbon dioxide emissions. The error correction model (ECM = −0.4739) indicates that 47.39% of a shock in the carbon dioxide emissions variable is resolved in one year and after 2 years, carbon dioxide emissions return to long term equilibrium.

China has been famous for its porcelains for millennia, and the combustion processes of porcelain production emit substantial amounts of air pollutants, which have not been well understood. This study provided firsthand data of air pollutant emissions from biomass porcelain kilns. The emission factor of PM₂.₅ was 0.95 ± 1.23 g/kg during the entire combustion cycle, lower than that of biomass burning in residential stoves and coal burning in brick kilns, attributed to the removal effects of the long-distance transport in dragon kilns. The temporal trend of particle pollutants, including particulate matters (PMs) and particulate polycyclic aromatic hydrocarbons (PAHs) (low at ignition phase and high at the end) again indicated the removal effects of the special structure, while gaseous pollutants, such as gaseous PAHs, exhibited the opposite result. The GWC₁₀₀ was estimated as 1.4 × 10⁶ and 0.5 × 10⁶ kg CO₂e/yr for the scenarios in which 50% and 100% of the wood was renewable, respectively. The GWC₁₀₀ of dragon kilns is nearly equal to that of 745 households using wood-fueled stoves. These results indicate the necessity of pollution controls for biomass porcelain kilns to estimate the emission inventory and climate change.

Air pollution constitutes the greatest environmental threat to human health in the European Union. In Poland, the emission of particulate matter and harmful gases originating from local coal based boiler plants and the combustion of fuels in residential heating appliances is a considerable source of air pollution. The combustion of fuel in home furnaces is inefficient due to the use of cheap fuels of low heating parameters and the frequent addition of waste. For the purpose of the research, deciduous tree wood pellets were selected as the basic fuel with the admixture of plastic waste, rubber, waste paper, wood residues, diapers, textile waste, multi-material packaging, construction waste, biomass and alternative fuel (RDF). Examining ash samples to confirm the practices of combusting or co-combusting waste materials in heating appliances is considered to be one of the most reliable detection methods; however, the results of direct research require further data processing. The application of hierarchical clustering analysis to the obtained results arranged into a matrix enabled in a simple way to demonstrate the similarities between the examined samples of fuel and the samples of fuel mixed with waste materials in the parameters space as well as to analyze the similarities among the measured parameters (the content of particular elements in ash) in the space of the examined samples. The application of chemometric methods for the purpose of identifying the combusted fuels, and, in particular the co-combusted waste complements the currently used monitoring tools which control the use of low quality fuels or the combustion of waste of different origin.

In recent years, severe air pollution still frequently occurs in winter despite the effective implementation of clean air actions in China. Therefore, field measurements of particle composition and gas precursors were collected from December 1, 2018 to January 15, 2019 at an urban site in a central Chinese city to investigate the existing mechanisms of pollution. The hourly averaged PM₂.₅ concentration during the campaign was 92.7 μg m⁻³, with nitrate and organic aerosol (OA) demonstrated as the principal components. Generally, NO₂ oxidation in the daytime was observed as the major mechanism for nitrate generation, and aerosol water content (AWC) showed its influential role with the associated increases in the nitrogen oxidation and nitrate partitioning ratios. When AWC increased from dozens to hundreds of μg m⁻³ after the afternoon, nocturnal N₂O₅ hydrolysis was demonstrated as the overriding mechanism and provoked extreme contamination of nitrates. Five sources of organic aerosols (OAs) were identified: hydrocarbon-like OAs (HOAs, 16.5%), coal combustion OAs (CCOAs, 19.2%), biomass burning OAs (BBOAs, 9.9%), semi-volatile oxygenated OAs (SV–OOAs, 29.4%), and low-volatile oxygenated OAs (LV-OOAs, 25.0%). SV-OOAs and LV-OOAs were identified as gasSOAs and aqSOAs according to their sensitivities to the atmospheric oxidation capacity and AWC. In addition, aqueous-phase processing was found to be the dominant pathway for SOA formation when the AWC concentration was higher than 80 μg m⁻³. As an influential factor for nitrate and SOA formation, AWC could be greatly affected by RH and the concentrations of inorganic species. Sulfate, which was mainly contributed by anthropogenic emissions, was demonstrated to be a significant factor for active aqueous phase reactions, although SO₂ has been dramatically reduced in recent years. Above all, this study revealed the significant role of AWC in current pollution episode in winter, and will assist in establishing future measures for pollution mitigation.

PM₂.₅ in Shijiazhuang was collected from October 15, 2018 to January 31, 2019, and selected toxic elements were measured. Five typical haze episodes were chosen to analyze the health risks and critical risk sources. Toxic elements during the haze episodes accounted for 0.33% of PM₂.₅ mass. Non-cancer risk of toxic elements for children was 1.8 times higher than that for adults during the haze episodes, while cancer risk for adults was 2.5 times higher than that for children; cancer and non-cancer risks were primarily attributable to As and Mn, respectively. Health risks of toxic elements increased during the growth and stable periods of haze episodes. Non-cancer and cancer risks of toxic elements during the haze stable periods were higher than other haze stages, and higher for children than for adults during the stable period. Mn was the largest contributor to non-cancer risk during different haze stages, while As was the largest contributor to cancer risk. Crustal dust, vehicle emissions, and industrial emissions were critical sources of cancer risk during the clean-air periods; while vehicle emissions, coal combustion, and crustal dust were key sources of cancer risk during the haze episodes. Cancer risks of crustal dust and vehicle emissions during the haze episodes were 2.0 and 1.7 times higher than those in the clean-air periods. Non-cancer risks from emission sources were not found during different periods. Cancer risks of biomass burning and coal combustion increased rapidly during the haze growth period, while that of coal combustion decreased sharply during the dissipation period. Vehicle emissions, crustal dust, and coal combustion were significant cancer risk sources during different haze stages, cancer risk of each source was the highest during the stable period. Southern Hebei, Northern and central Shaanxi were potential risk regions that affected the health of both adults and children in Shijiazhuang.