Characteristics of PM2.5 and PM10 pollution in the urban agglomeration of Central Liaoning

Ma, Yunfeng; Zhao, Huijie; Liu, Qiyao

doi:10.1016/j.uclim.2022.101170

Cited by 8 publications

(3 citation statements)

References 17 publications

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“…The average wind speed in autumn is the lowest among the seasons, and the stable atmospheric stratification make it difficult for pollutants to disperse. In addition, previous studies showed that, unlike winter and spring, particulate matter pollution in Liaoning was affected by the input of external polluted air masses, and local emissions were the main source in autumn [61]. Our results also supported this, where predictor variables such as pop_count, LST, NO 2 _TC, and HCHO_TC were retained in the fall model and could be regarded as factors linked to human activity and local emissions.…”

Section: Interpretation Of the Impact Factorssupporting

confidence: 86%

Spatial Patterns and Determinants of PM2.5 Concentrations: A Land Use Regression Analysis in Shenyang Metropolitan Area, China

Shi,

Zhang,

Yuan

et al. 2024

Sustainability

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Identifying impact factors and spatial variability of pollutants is essential for understanding environmental exposure and devising solutions. This research focused on PM2.5 as the target pollutant and developed land use regression models specific to the Shenyang metropolitan area in 2020. Utilizing the Least Absolute Shrinkage and Selection Operator approach, models were developed for all seasons and for the annual average, explaining 62–70% of the variability in PM2.5 concentrations. Among the predictors, surface pressure exhibited a positive correlation with PM2.5 concentrations throughout most of the year. Conversely, both elevation and tree cover had negative effects on PM2.5 levels. At a 2000 m scale, landscape aggregation decreased PM2.5 levels, while at a larger scale (5000 m), landscape splitting facilitated PM2.5 dispersion. According to the partial R2 results, vegetation-related land use types were significant, with the shrubland proportion positively correlated with local-scale PM2.5 concentrations in spring. Bare vegetation areas were the primary positive factor in autumn, whereas the mitigating effect of tree cover contrasted with this trend, even in winter. The NDVI, an index used to assess vegetation growth, was not determined to be a primary influencing factor. The findings reaffirm the function of vegetation cover in reducing PM2.5. Based on the research, actionable strategies for PM2.5 pollution control were outlined to promote sustainable development in the region.

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Section: Interpretation Of the Impact Factorssupporting

confidence: 86%

Spatial Patterns and Determinants of PM2.5 Concentrations: A Land Use Regression Analysis in Shenyang Metropolitan Area, China

Shi,

Zhang,

Yuan

et al. 2024

Sustainability

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“…These points belong both to the residential areas, such as Hotel Cetate and Central Park, and economic activities areas, such as Railway Station Square and Bus Station or Dedeman Market. Some of the literature data mention lower levels of particulate matter pollution in residential areas [37,38], but, in fact, the values are related to the low traffic. Measurements effectuated in the May campaign show that the pollutant emission level is strongly dependent on the number of cars per 10 min.…”

Section: Environmental Parameter Measurementsmentioning

confidence: 99%

Physicochemical Assessment of the Road Vehicle Traffic Pollution Impact on the Urban Environment

et al. 2023

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Vehicle traffic pollution requires complex physicochemical analysis besides emission level measuring. The current study is focused on two campaigns of emissions measurements held in May and September 2019 in Alba Iulia City, Romania. There was found a significant excess of PM2.5 for all measuring points and PM10 for the most circulated points during May, along with significant VOC and CO2 emissions. September measurements reveal threshold excess for all PM along with increased values for VOC and CO2 emissions. These are the consequences of the complex environmental interaction of the traffic. Street dust and air-suspended particle samples were collected and analyzed to evidence the PM2.5 and PM10 sources. Physicochemical investigation reveals highly mineralized particulate matter: PM2.5 fractions within air-suspended particle samples predominantly contain Muscovite, Kaolinite, and traces of Quartz and Calcite, while PM10 fractions within air-suspended particle samples predominantly contain Quartz and Calcite. These mineral fractions originate in street dust and are suspended in the atmosphere due to the vehicles’ circulation. A significant amount of soot was found as small micro-sized clusters in PM2.5 and fine micro-spots attached over PM10 particles, as observed by Mineralogical Optical Microscopy (MOM) and Fourier Transformed Infrared Spectroscopy (FTIR). GC-MS analysis found over 53 volatile compounds on the investigated floating particles that are related to the combustion gases, such as saturated alkanes, cycloalkanes, esters, and aromatic hydrocarbons. It proves a VOC contamination of the measured particulate matters that make them more hazardous for the health. Viable strategies for vehicle traffic-related pollutants mitigation would be reducing the street dust occurrence and usage of modern catalyst filters of the combustion gas exhausting system.

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“…At the same time, technological advancement and increased innovation levels play a crucial role in pollution control [12]. The industry provides a collaborative innovation environment for enterprises in the agglomeration area through technology spillover, which enhances the efficiency of clean technology R&D and promotes pollution reduction [13]. Therefore, industrial agglomeration and emission reduction may be intrinsically linked.…”

Section: Introductionmentioning

confidence: 99%

Does Innovative Industrial Agglomeration Promote Environmentally-Friendly Development? Evidence from Chinese Prefecture-Level Cities

Liu

et al. 2022

Sustainability

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China has promised to meet the “carbon peaking and carbon neutrality” goals. Exploring the relationship between innovative industrial agglomeration and environmental pollution plays an important role in the realization of these goals and sustainable development. Based on the panel data of 277 prefecture-level cities in China from 2007 to 2019, this paper uses the multi-period difference-in-difference (DID) model to examine the impact and mechanism of the innovative industrial agglomeration pilot (IIAP) policy on the environment. Furthermore, we explore the spatial spillover effect of the IIAP using spatial DID. The findings show that, firstly, the IIAP policy significantly contributes to environmentally-friendly development in terms of enhancing carbon emission efficiency (CEE) and reducing environmental pollution index (EPI). Secondly, the IIAP policy promotes environmentally-friendly development mainly by improving the technological innovation level. Additionally, the heterogeneity analysis shows that the environmentally-friendly effect of the IIAP policy is primarily in the eastern region, large cities, and non-resource-based cities. Finally, there is a significant spatial effect of the IIAP policy on environmentally-friendly development, mainly reflected in the weak siphon effect between treatment group cities and neighboring regions. We suggest that the government should continue to maintain the steady growth of the IIAP cities and improve the energy utilization efficiency through a policy of green technology innovation. The government should also optimize the spatial layout of the pilot cities and make full use of the energy advantages of each region to better promote environmentally-friendly development.

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Characteristics of PM2.5 and PM10 pollution in the urban agglomeration of Central Liaoning

Cited by 8 publications

References 17 publications

Spatial Patterns and Determinants of PM2.5 Concentrations: A Land Use Regression Analysis in Shenyang Metropolitan Area, China

Spatial Patterns and Determinants of PM2.5 Concentrations: A Land Use Regression Analysis in Shenyang Metropolitan Area, China

Physicochemical Assessment of the Road Vehicle Traffic Pollution Impact on the Urban Environment

Does Innovative Industrial Agglomeration Promote Environmentally-Friendly Development? Evidence from Chinese Prefecture-Level Cities

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