Industrial Dust Emissions Research Articles

Navigating urban risks for sustainability: A comprehensive evaluation of urban vulnerability based on a pressure–sensitivity–resilience framework

Cities are important symbols of civilization in human society. The vulnerability to cities caused by human activities and natural disasters has become increasingly evident. How to reduce the vulnerability of cities is an important topic in the research of urban public safety and sustainable development. In this study, a comprehensive evaluation of urban vulnerability is conducted on the basis of the pressure–sensitivity–resilience framework from a complex systems perspective, integrating three subsystems—the resource–environment, economic, and social subsystems. On the basis of data from 18 cities in Sichuan Province, China, from 2006 to 2021, this study analyzes vulnerability in terms of its scores, spatial and temporal evolution, and obstacles. The results reveal that the overall vulnerability of the Sichuan Basin has shown a fluctuating downward trend over the past sixteen years, and the spatial distribution has evolved into a large “low-vulnerability” agglomeration. The obstacles affecting urban vulnerability are also changing dynamically and include factors such as the harmless treatment rate of household waste and industrial smoke dust emissions. Drawing from these insights, this study enables the identification and diagnosis of urban vulnerability and, further, provides city managers with tailored recommendations for crafting policies that aim to mitigate risks and promote sustainable development.

Aluminum dust concentration detection based on LSTM-Kalman filter

Industrial dust emissions present serious hazards, including respiratory issues and explosion risks. Traditional dust concentration detection methods are often compromised by environmental factors. This study introduces a novel FFT-KF-LSTM-NET model to predict high-concentration aluminum powder levels, utilizing 128 sets of electrostatic induction measurement data. By applying the Fast Fourier Transform (FFT) to eliminate low-frequency interference, integrating Long Short-Term Memory (LSTM) networks for advanced time series analysis, and using the Kalman Filter (KF) for rapid model convergence, this approach significantly enhances prediction accuracy. The model achieves an 82% improvement in Mean Squared Error (MSE), reducing it to 0.1336, outperforming traditional methods. Furthermore, by modeling the voltage signal generated by charged dust particles in the electrostatic induction sensor's sensing area and using the first derivative of the voltage signal as a learning feature, the model's prediction speed is increased from 1.5 s-2 s–0.5 s, with improved anti-interference capabilities. These advancements position the FFT-KF-LSTM-NET model as a crucial tool for real-time, reliable dust concentration detection in industrial environments.

Research on Air Quality in the Pearl River Delta Region Based on Grey Relational Analysis

Based on the air quality monitoring data of the Pearl River Delta, the correlation between the impact of urban economic development and air quality influencing factors was explored through grey correlation analysis. The results showed that the main pollutants of air quality in the Pearl River Delta region are SO2, NO2, PM10, PM2.5, CO and O3. The main influencing factors of SO2, NO2, PM10, PM2.5, and CO are forest coverage, permanent population, and industrial smoke and dust emissions. The influencing factors of CO and O3 are similar, mainly including gross domestic product, gross industrial output, and the number of motor vehicles.

Role of low-density lipoprotein in mediating the effect of air pollution on coronary heart disease: a two-step multivariate Mendelian randomization study.

Air pollution is affecting the health of millions of people all over the world. The causal correlations of PM2.5, PM10, and nitrogen dioxide (NOx), as the main fine particulate matter, and coronary heart disease (CHD) are yet to be explored. Low-density lipoprotein (LDL) has been a principal factor in the pathogenesis of CHD. It is an interesting issue to consider whether LDL mediates the effect of air pollutants in CHD pathogenesis. A genome-wide association study (GWAS) on the European population, followed up from 2010 to 2018, involving over 400,000 participants, was based on a land-use regression model. The annual mean concentrations of major air pollutant particles, PM2.5 (n=423,796), PM10 (n=423,796), and NOx (n=456,380), were recorded. The large GWAS database of CHD covered over ten million SNPs with independent single nucleotide polymorphisms (SNPs). LDL database collected major biochemical blood parameters from over 400,000 patients (n=440,546). Taken together, we conducted independent two-sample Mendelian randomization (MR) analyses for the causality between air pollutants (PM2.5, PM10, and NOx) and CHD. Multivariate MR analysis was conducted using causal relationships to determine the direct effects of exposure on outcome. The fixed-effect inverse variance weighted (IVW2) method was mainly employed to assess this relationship, with a confidence interval of 95% for the odds ratio (OR). Also, MR-Egger, weighted median, maximum likelihood ratio method, and random-effects inverse variance-weighted (IVW1) method were adopted as supplementary methods. Two-sample MR results based on the IVW2 method suggested positive correlations between PM2.5 and CHD [OR 1.875 (1.279-2.748), p=0.001], PM10 and CHD [OR 2.586 (1.479-4.523), p=0.001], and NOx and CHD [OR 2.991 (2.021-4.427), p=4.37E-08]. The direct effect and mediating proportion were calculated using multivariable Mendelian randomization (MVMR). Lastly, the mediating proportions of LDL in the regulatory roles of PM2.5, PM10, and NOx in CHD were 2.82%, 4.73%, and 9.54%, respectively. PM2.5, PM10, and NOx share direct causal associations with CHD, and LDL performs a mediating role in this pathogenic process. Early prevention against air pollution (such as increasing green areas and reducing large-scale industrial dust emissions) and early lipid-lowering treatment can effectively prevent the occurrence of CHD.

PROFOUND INVESTIGATION OF DUST CHEMICAL COMPONENT IN INDUSTRIAL EMISSIONS FOR CORRECT ESTIMATION OF GEOECOLOGICAL IMPACT AND MONITORING

Background. Effective management of dust emissions from industrial enterprises should be based on reliable data on emission sources and emitted components. Correct estimation of geoecological impacts exerted by dust emissions is a complicated process due to chemical diversity of the soil component in them.
 Aim. The aim was to test a practical approach to identifying actual ambient air pollution with solid particles in a zone influenced by an economic entity for correct estimation of impacts and monitoring of ambient air quality.
 Materials and methods. Samples of industrial dust emissions were analyzed with a scanning electronic high-resolution microscope (magnification was from x5 to x300,000; acceleration voltage varied between 0.3 to 30 kW) with S3400N HITACHI x-ray fluorescent device (the limit of detection was approximately 5–10 mass % and the minimum field of view was 100 µm). X-ray photographs were processed by using XRD 6000/7000 software, Version 5.21. The results obtained by calculating dispersion of the dust component were mapped with ArcView 3.2 and ArcGIS 9.3.1., GIS-platforms created by ESRI.
 Results. Complex investigations of dust emissions were performed at a selected enterprise and this made it possible to identify a profile of the dust component in emissions from major sources. Actual composition of dusts emitted by the analyzed enterprise was established to differ fundamentally from the data declared in the inventory lists of emissions issued by the enterprise. The results of dispersion calculations gave grounds for spotting out substances that were priority (marker) ones for the analyzed production and we also estimated actual effects produced by dust emissions on ambient air.
 Conclusions. The study results allow concluding that a dust emission profile is a reliable instrument for estimating actual impacts of an industrial enterprise on ambient air. It can be applied to solve tasks within setting standards, monitoring and estimating actual impacts exerted by anthropogenic dust emissions when environmental measures are being planned and developed.

Does central ecological transfer payment enhance local environmental performance? Quasi-experimental evidence from China

Central transfer payment for the key ecosystem zones has become the most funded payments for ecosystem services program in China. The ecological fiscal transfer (EFT) aims to improve the eco-environmental quality of the targeted counties by providing supplementary fiscal funds, though not strictly specifying the usage. This study employs a time-varying difference-in-difference strategy to investigate the impact of EFT on environmental outcome by using a comprehensive county-level dataset covering 1949 counties from 2004 to 2015. Estimates show that the policy had a positive impact on local air quality, whereas the dynamic effect is diminishing. The policy effect is achieved through more stringent environmental regulation and stricter industrial access. Reduction of industrial dust emission is more noticeable than that of sulfur dioxide. There is an economic scale effect that the scale of a county can increase effectiveness of EFT on air quality improvement, whereas an opposite development stage effect will undermine its effectiveness. Heterogeneities were detected concerning transfer intensity, intervention period, geographical region, and ecosystem type. These findings facilitate a deep understanding how EFT could play a significant role in protecting local environment in large developing countries. Several policy implications are drawn to enhance the effectiveness of the largest EFT program.

Ownership structure and air pollution: The mediation effect of energy efficiency

There is no consensus on whether state-owned enterprises (SOEs) or privately-owned enterprises (POEs) pollute more. This study explores the impact of ownership on pollution emission intensity using micro-data from Chinese industrial enterprises. From the perspective of energy efficiency, the mechanism of ownership affecting pollution emissions is explored further. Research results show that the pollution emission intensity of SOEs is significantly higher than that of POEs. The underlying reason is the low energy efficiency of SOEs, and energy efficiency plays an important mediating role in the relationship between ownership and pollution emissions. Among industrial waste gas, nitrogen oxides (NOx) and dust emissions, energy efficiency plays the largest mediating effect between ownership and NOx emissions. Additionally, in both high-polluting and low-polluting industries, SOEs’ pollutant emission intensity is higher than that of POEs, however, the mediation effect of energy efficiency is greater in low-polluting industries. In cities with high growth pressure, SOEs’ pollutant emission intensity is more significant than that of POEs. On the contrary, there are no noticeable differences in pollutant emission intensity between SOEs and POEs in cities with low growth pressure. But the mediation effect of energy efficiency is more significant in cities with high growth pressure. Industrial enterprises are the ultimate sources of industrial pollution. Therefore, the formulation of effective environmental policies cannot be separated from the analysis of enterprises’ emission behaviors and the assessment of micro factors affecting emissions. The conclusions of this study provide a basis for developing countries to formulate environmental policies for industrial enterprises.

The evolution and determinants of Chinese inter-provincial green development efficiency: an MCSE-DEA-Tobit-based perspective.

Continuous and rapid economic development has brought about excessive resource consumption and environmental pollution. Therefore, it is particularly essential to coordinate economic, resource, and environmental factors to achieve sustainable development. This paper develops a new data envelopment analysis (DEA) method that can be used for multi-level complex system evaluation (MCSE-DEA) to reveal the inter-provincial green development efficiency (GDE) in China from 2010 to 2018. Moreover, the Tobit model is applied to explore the influencing factors of GDE. We found that (i) the MCSE-DEA model tends to have lower efficiency scores than the traditional P-DEA (panel data envelopment analysis) model, and the top three provinces are Shanghai, Tianjin, and Fujian; (ii) the efficiency shows an increasing trend during the whole study period. The southeast region and the Middle Yangtze River region have the highest efficiency values, reaching 1.09, while the northwest region ranks last with an average efficiency value of 0.66. Shanghai performs the best, while Ningxia performs the worst, with efficiency values of 1.43 and 0.58, respectively; (iii) the provinces with lower efficiency values mainly come from economically underdeveloped remote regions, which can be attributed to issues of water consumption (WC) and energy consumption (EC). Moreover, there are much room for improvement in solid waste emissions (SW) and soot and industrial dust emissions (SD); (iv) the environmental investment, R&D investment, and economic development level can significantly improve GDE, while industrial structure, urbanization level, and energy consumption have inhibiting effects.

Multi-element features and trace metal sources of road sediment from a mega heavy industrial city in North China

As the primary carrier of harmful elements, road sediment poses severe hazards to human health and ecological environment, especially in megacities. Based on the industrial cities in North China, this research focused on the multi-element features and the pollution levels, sources, and spatial distributions of trace metals in road sediment of Shijiazhuang. The mean levels of P (928.4 mg kg−1), S (1446.2 mg kg−1), Cl (783.9 mg kg−1), Br (5.3 mg kg−1), Na2O (2.0%), CaO (9.9%), Co (36.0 mg kg−1), Pb (38.0 mg kg−1), Cu (34.7 mg g−1), Zn (149.1 mg kg−1), Ba (518.1 mg kg−1), and Sr (224.9 mg kg−1) in road sediment were greater than their soil background values. Trace metals in most samples was moderately (75%) and heavily contaminated (15.6%). The industrial areas, congested roads, and residential areas in the northeast, middle and south of Shijiazhuang are the hotspots of trace metals pollution. A comprehensive analysis of trace metals sources indicated that Ni, V, Ga, Rb, Y, Sc, La, Ce, Zr, and Hf were mainly from natural source, which contributed to 34.2% of the total trace metals concentrations. Cu, Pb, Zn, Cr, Ba, Sr, and Mn primarily originated from mixed source, which accounted for 46.5%. Co principally came from building source, which accounted for 19.3%. This study shows that industrial discharges, construction dust and traffic emissions are the primary anthropogenic sources of trace metals in road sediment in the study area.

ONCOLOGICAL DISEASES ASSOCIATED WITH ADVERSE ENVIRONMENTAL CONDITIONS IN THE REPUBLIC OF NORTH OSSETIA - ALANIA

Abstract. The atmospheric air of the Republic of North Ossetia - Alania is periodically polluted with sulfur dioxide, carbon monoxide, nitrogen dioxide, nitrogen oxide, benzapyrene, hydrogen chloride, ammonia, lead, cadmium and zinc. Sources of pollution are the metalworking, woodworking industries, forestry and fuel economy, production of building materials. Environmental pollution is the cause of a number of environmentally-related diseases, including malignant neoplasms. The purpose of the study: to study the relationship between air pollution and cancer in the Republic of North Ossetia-Alania. To achieve this goal, epidemiological and sanitary-statistical research methods based on data from official documents and reports were used. The results of the study showed that industrial dust, aerosols and vehicle emissions released into the atmospheric air exceed the MPC, which leads to environmental pollution. In 2020, the share of atmospheric air samples exceeding the maximum one-time MPCs on highways and in the residential area was for suspended solids (2.8%), carbon monoxide (1.4%) and nitrogen dioxide (1.4%). The data obtained indicate the deterioration of the environmental situation, where the atmospheric air is a complex mixture of a wide range of carcinogenic and mutagenic substances that promote the growth of malignant neoplasms. In 2020, malignant neoplasms were first detected in 1974 cases, which is 283.2 per 100 thousand of the population, and in 2019 there were 2132 cases - 334.4. The first ranking place is occupied by breast cancer, followed by skin, trachea, bronchi, lung, colon, prostate, body of the uterus, stomach, rectum. Thus, there is a deterioration of the environmental situation due to air pollution and an increase in the level of both general and primary incidence of malignant neoplasms.

How does high-speed rail construction affect air pollutant emissions? Evidence from the Yangtze River Delta Urban Agglomeration in China

Taking the construction of high-speed rail as a “quasi-natural experiment”, the panel data of 26 cities in the Yangtze River Delta from 2004 to 2018 were selected as samples, and a difference-in-differences model was constructed to study the impact of high-speed rail construction on air pollutant emissions. Furthermore, the meditating effect model and difference-in-differences model were built to explore the paths of high-speed railway construction affecting air pollutant emissions. According to the study, the construction of high-speed rail reduces industrial sulfur dioxide emissions and increases the emission of industrial smoke and dust, which are more obvious in areas with good economic conditions. The role of high-speed rail in reducing emissions is realized through the structure effect, technological effect and substitution effect. However, the construction/renovation process of high-speed rail lines or stations does increase the industrial smoke and dust emissions. In this study, the bidirectional effects of high-speed rail construction on different air pollutant emissions were identified, including the high-speed rail construction process into the research. Multiple paths of action were proposed, bridging the gap of existing studies. The study reveals that controlling the air pollution emissions throughout the full life cycle of the high-speed rail, from the construction process to its operation, was essential.

Quantitative Assessment of the Ecological Vulnerability of Baiyangdian Wetlands in the North China Plain

Quantitative assessment of vulnerability is a core aspect of wetland vulnerability research. Taking Baiyangdian (BYD) wetlands in the North China Plain as a study area and using the ‘cause-result’ model, 23 representative indicators from natural, social, sci-tech and economic elements were selected to construct an indicator system. A weight matrix was obtained by using the entropy weight method to calculate the weight value for each indicator. Based on the membership function in the fuzzy evaluation model, the membership degrees were determined to form a fuzzy relation matrix. Finally, the ecological vulnerability was quantitatively assessed based on the comprehensive evaluation index calculated by using a composite operator to combine the entropy weight matrix with the fuzzy relation matrix. The results showed that the ecological vulnerability levels of the BYD wetlands were comprehensively evaluated as Grade II, Grade III, Grade IV, and Grade III in 2010, 2011–2013, 2014, and 2015–2017, respectively. The ecological vulnerability of the BYD wetlands increased from low fragility in 2010 to general fragility in 2011–2013, and to high fragility in 2014, reflecting the fact that the wetland ecological condition was degenerating from 2010 to 2014. The ecological vulnerability status then turned back into general fragility during 2015–2017, indicating that the ecological situation of the BYD wetlands was starting to improve. However, the ecological status of the BYD wetlands on the whole is relatively less optimistic. The major factors affecting the ecological vulnerability of the BYD wetlands were found to be industrial smoke and dust emission, wetland water area, ammonia nitrogen, total phosphorus, rate of industrial solid wastes disposed, GDP per capita, etc. This illustrates that it is a systematic project to regulate wetland vulnerability and to protect regional ecological security, which may offer researchers and policy-makers specific clues for concrete interventions.

Tobacco Industry Agglomeration and Industrial Pollution Emission: Nonlinear Test Based on Panel Data

In the past 40 years, the agglomeration of tobacco industry plays a vital role in economic growth in China. Meanwhile, the rapid economic development has paid serious environmental and energy costs.Based on the panel data of 31 provinces in China from 2005 to 2015, this paper uses the differential GMM method to empirically test the relationship between the agglomeration of tobacco industry and industrial pollution emissions. The study found that the spatial agglomeration of the tobacco industry has a significant negative impact on industrial wastewater, sulfur dioxide and industrial dust emissions. Capital labor, enterprise scale, and pollution control investmentall have a significant impact on pollution emissions.Therefore, the increase in the agglomeration of China’s tobacco industry is conducive to reducing industrial pollution emissions.

Spatiotemporal Evolution and Trend Prediction of Tourism Economic Vulnerability in China’s Major Tourist Cities

The evaluation and trend prediction of tourism economic vulnerability (TEV) in major tourist cities are necessary for formulating tourism economic strategies scientifically and promoting the sustainable development of regional tourism. In this study, 58 major tourist cities in China were taken as the research object, and an evaluation index system of TEV was constructed from two aspects of sensitivity and adaptive capacity. On the basis of the entropy weight method, TOPSIS model, obstacle diagnosis model, and BP neural network model, this study analyzed the spatiotemporal patterns, obstacle factors, and future trends of TEV in major tourist cities in China from 2004 to 2019. The results show three key findings: (1) In terms of spatiotemporal patterns, the TEV index of most of China’s tourist cities has been on the rise from 2004 to 2019. Cities throughout the coast of China’s Yangtze River Delta and the Pearl River Delta urban agglomeration show high vulnerability, whereas low vulnerability has a scattered distribution in China’s northeast, central, and western regions. (2) The proportion of international tourists out of total tourists, tourism output density, urban industrial sulfur dioxide emissions per unit area, urban industrial smoke and dust emission per unit area, and discharge of urban industrial wastewater per unit area are the five major obstacles affecting the vulnerability degree of the tourism economy. (3) According to the prediction results of TEV from 2021 to 2030, although the TEV of many tourist cities in China is increasing year by year, cities with low TEV levels occupy the dominant position. Research results can provide reference for tourist cities to prevent tourism crises from occurring and to reasonably improve the resilience of the tourism economic system.

Pilot scale test of wet dust removal by high gravity intensification technology in fertilizer plant

Industrial dust can cause serious harm to the environment and human body. High gravity wet dust removal is a new type of high-efficiency dust removal technology, with the advantages of high dust removal efficiency, low economic cost, convenient operation and maintenance. In this work, a cross-flow rotating packed bed was used as the wet dust removal equipment, and a pilot scale dust removal experiment platform was built at the production site of the enterprise. The dust removal effect of high gravity wet dust removal technology on granulation waste gas in actual production was also studied. The second compound fertilizer plant of TianJi Group emitted dust-containing exhaust gas with a dust content of about 2500 mg/m3 during the production process. Different key parameters including high gravity factor, liquid flow rate and liquid circulation time were investigated on dust removal efficiency and fractional efficiency, and the mechanism of high gravity wet dust removal was analyzed. The obtained results suggested that under the conditions of gas flow rate of 400 m3/h, liquid flow rate of 0.5 m3/h and high gravity factor of 205.61, the dust removal rate was as high as 99.88% with an outlet concentration of less than 10 mg/Nm3. Under three hours of clean water absorption cycle, the dust concentration after purification could still be reduced to less than 10 mg/Nm3, and the dust removal efficiency could reach more than 99%. The relationship between the fractional efficiency of the cross-flow rotating packed bed and the dust particle size was nonlinearly fitted, which showed a good fit. High gravity wet dust removal technology increased the inertial force of particles in the gas through rotation, while atomizing the liquid into a micro liquid. The scales of the two were matched, and the inertial collision was effectively enhanced to improve the dust capture effect. Therefore, high gravity wet dust removal technology can effectively control industrial dust emissions and has a strong potential for industrial applications.

Assessing sustainability environmental performance of three urban agglomerations in China: An input–output modeling approach

As a special form of a cluster city, urban agglomeration has become an important platform to support national economic growth and to participate in international competition and cooperation, but it faces severe environmental problems. This research thus selects panel data of 60 cities in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) from 2013 to 2017. Based on the input–output perspective, labor and energy consumption per GDP are selected as input indicators, GDP, PM2.5, SO2, industrial smoke and dust emissions, and wastewater discharged as output indicators, and fixed assets as a carry-over variable in the dynamic DEA model to evaluate and analyze the environmental efficiencies of these three urban agglomerations. Findings show that their total environmental efficiency exhibits a wave-like development trend, and that the total efficiency score of BTH is better than that of PRD and YRD. From the viewpoint of a sub-efficiency index, PM2.5 is the lowest in unexpected output, where its average five-year efficiency score is 0.9847, while the average score of industrial smoke and dust emissions efficiency is the lowest at 0.6199. Finally, this paper offers suggestions for different problems facing the three urban agglomerations.

Ecological Forecasting of Industrial Dust Emissions: Problems and Solutions

The results of the study of the levels of atmospheric air pollution by solid particles with different approaches to the accounting of dust and the analysis of the sufficiency and validity of permissible emission standards are presented. On the example of an operating enterprise, taking into account the current inventory, a comparative analysis of the levels of exposure to solid chemicals and the sum of all dusts (TSP) was performed. It is established that the dust factor at the total emission, forms the values of the maximum concentrations 2 times more than the individual chemical components. The presented results confirm the need to review the existing approaches to the regulation of emissions of solid components, including the inclusion in the system of the assessment of the sufficiency of emissions by the criterion of the total impact of dust in general. A correctly estimated level of total dust exposure will allow to exclude an unacceptable level of exposure to solid industrial emissions at the initial stage of the formation of project and environmental documentation (NDV projects).

Source analysis of heavy metals in atmospheric particulate matter in a mining city.

The enrichment of heavy metals in air-borne particulate matters poses a great threat to health. In order to understand the mineralogical characteristics and sources of heavy metals in atmospheric particulate matter in coal mining cities, PM2.5 (particulate matter with an aerodynamic diameter less than 2.5μm), PM10 (particulate matter with an aerodynamic diameter less than 10μm) and TSP (total suspended particulates) were sampled from Huainan city, China in December 2016 and May 2017. The contents of heavy metals in TSP are the highest, while those in PM2.5 are the lowest. Zn, Mn, and Pb are the main components of heavy metals in Huainan atmospheric particulates. Straw burning activities may result in relatively higher atmospheric particulate matter content in summer than that in winter. The proportion of mineral particles in the studied particulate matters was the highest (40.79%), followed by soot aggregates (35.55%) and coal fly ash (19.74%). The results of energy spectrum analysis show that the main component of soot aggregates is C, and other contents are contributed by elements such as O and Si. Coal fly ash mainly contains C, O, Si, and a small amount of Al and Na. As, Cd, and Hg are the most easily enriched heavy metals. Industrial emissions, traffic discharges, coal combustion and dust emissions were found to be the main sources of heavy metals in atmospheric particulates.

Can “energy saving and emission reduction” demonstration city selection actually contribute to pollution abatement in China?

The “National Comprehensive Demonstration City Selection of Energy Saving and Emission Reduction Fiscal Policy” (“ESER” demonstration city selection) is an important assessment-and-commendation policy to promote in-depth advancement of the construction of ecological civilization in China. Accurate evaluation of the environmental effect of the policy is of great significance to its promotion. A difference-in-differences (DID) model is used to explore the role of the “ESER” demonstration city policy in urban environmental governance. The results of empirical tests show that the policy has significantly reduced fine particulate matter (PM2.5), industrial dust, sulfur dioxide (SO2), and wastewater emissions by 39.1%, 61%, 18.3%, and 7.4%, respectively. The results of the multi-stage DID model show that the emission reduction effect of this policy increases significantly in the short term but decreases gradually in the long term. The results of the mediation effect model show that the emission reduction effect is driven mainly by increasing innovation capacity and reducing energy intensity; the effect is also more significant in cities on a larger scale, with higher levels of fiscal expenditure and financial development, more abundant human capital and higher levels of economic development. This study provides empirical support for China to further promote the assessment-and-commendation environmental policies represented by the “ESER” demonstration city policy nationwide.

A synthesis review on atmospheric wet deposition of particulate elements: scavenging ratios, solubility, and flux measurements

Atmospheric dry and wet deposition of particulate matter controls its lifetime in air and contributes to the environmental burden of toxic pollutants and thus has important implications on human and ecosystem health. This synthesis review focuses on atmospheric wet deposition of particulate elements and analyzed their scavenging ratios (i.e., ratio of concentration in precipitation to that in ambient air), solubility, and wet deposition flux measurements based on published studies in the literature, aiming to gather updated knowledge that can be used for modeling their wet deposition. Our analysis finds that scavenging ratios of a specific element have a narrow range. Overall, elemental scavenging ratios for snow are approximately three times higher than those for rain. Elements that are bound to coarse (PM2.5–10) particles have larger scavenging ratios than those bound to fine (PM2.5) particles, except for Fe and Si. Solubility of elements in rainwater ranges from 8% (Fe) to 94% (Ca). Solubility is moderately correlated with scavenging ratio, possibly explaining the lower scavenging ratios of Fe and Si compared with other elements with similar fine fractions. Data collected from North America, Europe, the Middle East, and Asia show that the wet fluxes of Al and Fe are orders of magnitude greater than those of routinely monitored anthropogenic elements (Zn, Pb, Cu, Ni, Cd, Cr). Wet deposition fluxes of particulate elements in the Middle East exceed those in other regions, likely due to regional transport of dust and soil resuspension. Fluxes from all regions are a factor of two to three times greater in industrialized and urban locations than in rural and remote locations because of industrial, vehicular, and soil and mineral dust emissions. Dry deposition fluxes are usually greater than wet deposition fluxes, although to varying degrees according to co-located measurements. Based on the relationships between scavenging ratio and the elemental PM2.5 fraction under rain and snow conditions, we derived regression equations for estimating scavenging ratios of particulate elements for which measurements are limited. Such knowledge and data improve the quantification of atmospheric deposition fluxes for an expanded list of metals and metalloids and the understanding of pathways contributing to ecological risk.