The Spatial-Temporal Characteristics and Influential Factors of NOx Emissions in China: A Spatial Econometric Analysis

Exploring the spatial effects and influencing mechanism of ozone concentration in the Yangtze River Delta urban agglomerations of China

Ground-level ozone (O3) pollution has emerged as a significant concern impacting air quality in urban agglomerations, primarily driven by meteorological conditions and social-economic factors. However, previous studies have neglected to comprehensively reveal the spatial distribution and driving mechanism of O3 pollution. Based on the O3 monitoring data of 41 cities in the Yangtze River Delta (YRD) from 2014 to 2021, a comprehensive analysis framework of spatial analysis-spatial econometric regression was constructed to reveal the driving mechanism of O3 pollution. The results revealed the following: (1) O3 concentrations in the YRD exhibited a general increasing and then decreasing trend, indicating an improvement in pollution levels. The areas with higher O3 concentration are mainly the cities concentrated in central and southern Jiangsu, Shanghai, and northern Zhejiang. (2) The change of O3 concentration and distribution is the result of various factors. The effect of urbanization on O3 concentrations followed an inverted U-shaped curve, which implies that achieving higher quality urbanization is essential for effectively controlling urban O3 pollution. Traffic conditions and energy consumption have significant direct positive influences on O3 concentrations and spatial spillover effects. The indirect pollution contribution, considering economic weight, accounted for about 35%. Thus, addressing overall regional energy consumption and implementing traffic source regulations are crucial paths for O3 pollution control in the YRD. (3) Meteorological conditions play a certain role in regulating the O3 concentration. Higher wind speed will promote the diffusion of O3 and increase the O3 concentration in the surrounding city. These findings provide valuable insights for designing effective policies to improve air quality and mitigate ozone pollution in urban agglomeration area.

Spatiotemporal pattern evolution and influencing factors of online public opinion--Evidence from the early-stage of COVID-19 in China

With the rapid development of internet information technology, online public opinion's influence is infinitely magnified, seriously threatening social security and national governance. It is significant to clarify the spatial and temporal evolution rules of online public opinion on major epidemics and its influencing factors for the governance and guidance of online public opinion on major epidemics. In this paper, the spatiotemporal evolution analysis model of online public opinion and an analysis model of influencing factors were constructed. We selected the Baidu index and microblog crawler text data at the early stage of COVID-19 as the research objects and analyzed the evolution of online public opinion during the time period by using the optimal segmentation method, spatial autocorrelation analysis, and text analysis method. The spatiotemporal evolutionary influences and their influence are further analyzed using the geographic probe factor detection method. The results showed that the evolution of online public opinion in the early stage of the epidemic was closely related to the event's evolution and the prevention and control effect. In the time dimension, the early evolution of online public opinion has prominent periodic characteristics. In the geospatial dimension, there are significant spatial agglomeration effects and spillover effects. In the cyberspace dimension, there are significant differences in online public opinion heat, hot topics, and netizens' emotional tendencies at different stages. Furthermore, the severity of the epidemic, the number of Internet users, the number of media reports and the region's attributes jointly affect the spatial and temporal evolution pattern of online public opinions about the epidemic. The research results provide decision-making references for the government and planners to effectively manage online public opinion on emergencies and improve the government's public opinion governance capacity and level.

Spatiotemporal variations of NO2 and its driving factors in the coastal ports of China

Nitrogen Dioxide (NO₂) is one of the major air pollutants in coastal ports of China. Understanding the spatiotemporal varying effects of driving factors of NO₂ is vital for the implementation of differentiated air pollution control measures for different port areas. Based on the Ozone Monitoring Instrument (OMI) satellite data, we adopted a Geographically and Temporally Weighted Regression (GTWR) model to explore the influences of meteorological and socioeconomic factors on the NO₂ Vertical Column Concentrations (VCDs) in coastal ports of China from 2015 to 2021. The results indicate that NO₂ VCD in most ports has decreased since 2016 and the ports with serious NO₂ pollution are mainly distributed in northern China. The associations between NO₂ VCD levels and their drivers exhibit obvious spatiotemporal heterogeneity. Higher wind speed and relative humidity are more helpful to alleviate NO₂ pollution in ports of the Bohai Rim and the Pearl River Delta. Cargo throughput has more closely associated with NO₂ pollution in Beibu Gulf in recent years, yet there is no significant association found for Shanghai ports. The positive relationship between transportation emissions and NO₂ VCD is more significant in southern ports. This work provides some implications for the formulation of targeted emission reduction policies for different ports along the Chinese coast.

The varying roles of the dimensions of affluence in air pollution: a regional STIRPAT analysis for Germany

STIRPAT models investigate the impacts of population, affluence, and technology on the environment, with most STIRPAT studies revealing positive impacts of both population and affluence. Affluence is commonly defined as GDP per capita, but investigations of its impact largely neglect the possibility that increasing prosperity affects the environment in varying-even opposing-ways. This study addresses this gap by decomposing affluence into three dimensions-income per taxpayer, private car ownership, and the share of single-family houses-and analyzing their roles in the production of local NO_x emissions. Results for 367 German districts and autonomous cities between 1990 and 2020 indicate that, while private car ownership and single-family houses per capita can be considered drivers of local pollutants, such is not the case for income per taxpayer, which we find has a negative impact on NO_x emissions. The empirical findings suggest that policies should strengthen integrated mobility concepts and establish incentives that favor investment in modern heating or self-sufficiency systems.

Contributions of cleaner production and end-of-pipe treatment to NOx emissions and intensity reductions in China, 1997-2018

The Chinese experience of economic development and environmental protection provides an important reference for developing countries. Although changes in aggregate NO_x emissions have been widely studied, there is a relative lack of studies analysing NO_x intensity changes and their related development strategies in China. This study attempts to identify the socioeconomic drivers and change patterns for both NO_x emissions and intensity considering the cleaner production and end-of-pipe treatments. Both structural decomposition analysis and structural path analysis were used to analyse the NO_x emissions/intensity changes at different levels and transmission layers in China in the last two decades (1997-2018). The results indicate that construction contributes the most to NO_x emissions/intensity, followed by transportation. The emission intensity effect is the primary driver of NO_x emissions/intensity reduction, which mainly benefits from end-of-pipe treatment and energy efficiency improvement. Especially, during 2012-2018, they decreased 11,916 Kt-NO_x and 8,103 Kt-NO_x emissions and aggregate embodied intensity by 43.2% and 29.8%, respectively. The final demand effect is the primary deterrent, which is attributed to investment and consumption effects. The critical sectors for future NO_x reduction are the construction and building materials industry, transportation and other services industry. The policy implications and recommendations for the future developments are discussed based on the study findings.

Influencing factors and trend prediction of PM2.5 concentration based on STRIPAT-Scenario analysis in Zhejiang Province, China

The government's development of eco-environmental policies can have a scientific foundation thanks to the fine particulate matter (PM2.5) medium- and long-term change forecast. This study develops a STRIPAT-Scenario analysis framework employing panel data from 11 cities in Zhejiang Province between 2006 and 2020 to predict the changing trend of PM2.5 concentrations under five alternative scenarios. The results reveal that: (1) urbanization development (P), economic development (A), technological innovation investment (T) and environmental regulation intensity have a significant inhibitory effect on PM2.5 concentration in Zhejiang Province, while industrial structure, industrial energy consumption and the number of motor vehicles (TR) have a significant increase on PM2.5 concentration. (2) Under any scenario, the PM2.5 concentration of 11 cities in Zhejiang Province can reach the constraint target set in the 14th Five-Year plan. The improvement in urban PM2.5 quality is most obviously impacted by the high-quality development scenario (S4). (3) Toward 2035, PM2.5 concentrations of 11 cities in Zhejiang Province can reach the National Class I level standard in most scenario models, among which Hangzhou, Jiaxing and Shaoxing are under high pressure to reduce emissions and are the key areas for PM2.5 management in Zhejiang Province. However, most cities cannot reach the 10 μg/m3 limit of WHO's AQG2005 version. Finally, this study makes recommendations for reducing PM2.5 in terms of enhancing industrial structure and funding science and technology innovation.

Spatial Effects of Urban Transport on Air Pollution in Metropolitan Municipalities of Mexico

The objective of this work was to estimate the local effects and spatial spillover effects of the number of vehicles, use of urban public transport, and population density on nitrogen oxide emissions for 405 metropolitan municipalities in Mexico in 2016. To this end, a Spatial Durbin Model was estimated. We found positive direct effects of the number of vehicles and population density and negative direct effects of the use of urban public transport. The number of vehicles in circulation had negative spillover effects on the nitrogen oxide emissions of neighboring municipalities. These results indicate that the design of public policy programs aimed at reducing air pollution in Mexico should be based on coordination across metropolitan municipalities.

Spatiotemporal Analysis of NO2 Production Using TROPOMI Time-Series Images and Google Earth Engine in a Middle Eastern Country

Like many developing countries, Iran faces air pollution, especially in its metropolises and industrial cities. Nitrogen dioxide (NO2) is one of the significant air pollutants; therefore, this study aims to investigate the spatiotemporal variability of NO2 using Tropospheric Monitoring Instrument (TROPOMI) sensor mounted on the Sentinel-5P (S5P) satellite and the Google Earth Engine (GEE) platform over Iran. In addition, we used ground truth data to assess the correlation between data acquired by this sensor and ground stations. The results show that there is a strong correlation between products of the TROPOMI sensor and data provided by the Air Quality Monitoring Organization of Iran. The results also display that the correlation coefficient (R) of NO2 between ground truth data and the TROPOMI sensor varies in the range of 0.4 to 0.92, over three years. Over an annual period (2018 to 2021) and wide area, these data can become valuable points of reference for NO2 monitoring. In addition, this study proved that the tropospheric NO2 concentrations are generally located over the northern part of Iran. According to the time and season, the concentration of the tropospheric NO2 column shows higher values during winter than in the summertime. The results show that a higher concentration of the tropospheric NO2 column is in winter while in some southern and central parts of the country more NO2 concentration can be seen in the summertime. This study indicates that these urban areas are highly polluted, which proves the impact of pollutants such as NO2 on the people living there. In other words, small parts of Iran are classified as high and very highly polluted areas, but these areas are the primary location of air pollution in Iran. We provide a code repository that allows spatiotemporal analysis of NO2 estimation using TROPOMI time-series images within GEE. This method can be applied to other regions of interest for NO2 mapping.

Accelerated reduction of air pollutants in China, 2017-2020

Emission regulations of the power and industry sectors have been identified as the major driver of PM_2.5 mitigation over China during 2013-2017. In this study, we use ground-based observations of four air pollutants (CO, NO₂, SO₂, and PM_2.5) to show that additional stringent emission policies on the industrial, transportation, and residential sectors during the new 3-year protection plan (2018-2020) have accelerated the improvement of China's air quality. Based on regional (North and South China) trends of annual mean measurements, significant reductions are observed for all four pollutants during 2017-2020. These decreasing trends are found to be >30% stronger than 2015-2017 for NO₂, CO, and PM_2.5. For CO and PM_2.5, the acceleration is the strongest in winter and North China, when and where the residential clean-heating actions were implemented. While for NO₂, the accelerations are pronounced regardless of region or season, reflecting nationwide measures to reduce NO_x emissions from industrial and transportation activities. SO₂ concentration reductions that were already substantial before 2017 are maintained but not accelerated, consistent with the dominance of end-of-pipe measures rather than a structural change of energy fuels. Our investigation highlights the value of multi-pollutant analysis to relate emission policies with air quality changes.

Does the Agglomeration of Producer Services and the Market Entry of Enterprises Promote Carbon Reduction? An Empirical Analysis of the Yangtze River Economic Belt

As the world’s largest carbon emitter, China has been committed to carbon emission reduction and green development. Under the goal of “double carbon”, adjusting the industrial structure and promoting the development of producer services are regarded as effective emission reduction paths. In this paper, from the perspective of market entry of enterprises, we firstly investigate the transmission mechanism between market entry of enterprises and industrial agglomeration and summarize the carbon emission reduction mechanism of producer services. Based on the panel data of 110 prefecture-level cities in China’s Yangtze River Economic Belt (YREB) from 2003 to 2017, we analyze the impact of producer services on carbon emission reduction by using the dynamic spatial panel model. The empirical results show that China’s urban carbon dioxide emissions have noticeable spatial spillover effects and high emission club clustering characteristics and exhibit a noticeable snowball effect and leakage effect in time and space dimensions. The development of the producer services can effectively reduce carbon emission levels, effectively solving the dilemma of “stabilizing growth and promoting emission reduction”. Furthermore, there is an apparent synergistic effect between enterprises’ market entry and industrial agglomeration. The agglomeration of producer services can effectively promote the entry of innovative new enterprises, thus increasing the carbon emission reduction effect. However, due to resource mismatch and isomorphic development, this carbon emission reduction effect has apparent industrial heterogeneity and regional heterogeneity. Finally, this paper makes suggestions for optimizing regional industrial structure, strengthening inter-regional linkage cooperation, and promoting the advanced development of the producer services.

Spatiotemporal characteristics of nitrogen dioxide pollution in mainland China from 2015 to 2018

With the rapid industrial development and urbanisation in China, nitrogen dioxide [Formula: see text] pollution has become a severe environmental problem that threatens public health. Based on hourly concentration monitoring data of the six main air pollutants in mainland China, a space-time Bayesian hierarchy model was employed to analyse the spatiotemporal trends of the absolute and relative [Formula: see text] concentrations (i.e., the proportion of [Formula: see text] in the six main air pollutants: [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]). Both the absolute and relative [Formula: see text] concentrations were higher in the autumn and winter of each year during the study period. Four regions in particular-the North China Plain, the Yangtze River Delta, the Sichuan Basin, and the Pearl River Delta-experience the largest amounts of [Formula: see text] pollution, with a high local magnitude of more than 1.0 relative to the overall absolute and relative [Formula: see text] concentrations; this affects an area with a human population of 571.85 million, which is 42.47% of the total population. Central China (i.e., the Shaanxi-Shanxi-Henan region) and the Tarim Basin (northwest of Xinjiang) were heavily polluted by [Formula: see text] and other pollutants throughout the year, with a high local magnitude of more than 1.0 relative to the overall absolute [Formula: see text] concentration. The [Formula: see text] pollution in most of the cities in western and southern China is less serious, along with cities in the northeast. Local trends reveal that in general, cities with high [Formula: see text] pollution are accompanied by upward trends. Specifically, except for in the summer, there were about 86 cities showing the increasing trend, of which 66 cities are located in areas with higher absolute and relative [Formula: see text] concentrations. Taiyuan, for example, represents the maximal local trend, with an average annual increase of 4.39 (95% CI 1.61-7.43) [Formula: see text] and 0.43 (95% CI 0.16-0.73) %, respectively, which will lead to further increases in the population exposure-risk in heavily polluted areas.

Socioeconomic factors of industrial air pollutants in Zhejiang Province, China: Decoupling and Decomposition analysis

In order to analyze and control air pollutant emissions effectively, on the basis of comprehensive consideration of three different pollution sources of industrial sulfur dioxide, industrial nitrogen oxides, and industrial smoke and dust, the Tapio decoupling model and LMDI decomposition model with six decomposition variables are constructed to compare the effects of socioeconomic factors on industrial air pollutant emissions in 11 cities in Zhejiang Province during 2006-2017. Then, a decoupling effort model is developed to analyze the effectiveness of the decoupling efforts taken at city level. This study found that (1) during the period of 2006-2017, the air pollutant emission reduction work in Zhejiang Province achieved remarkable results. More specifically, economic scale effect and population effect are the main factors for the increase of air pollutant emissions. And, the energy emission intensity effect and technological progress are the main driving forces for the reduction of three atmospheric pollutants, followed by the reduction effect of industrial structure and energy structure. (2) The environmental pollution problems of different air pollution sources in different cities are heterogeneous. (3) Eleven cities in Zhejiang Province have made significant decoupling efforts on the emission of three kinds of air pollutants, but there are some differences in the trend of the decoupling effort index of different pollution sources in different cities. In the future, illustrating by the example of Zhejiang, we should implement a "common but different" emission reduction strategy and emphasize pollutant emissions control during energy use in the efforts of further promoting the reduction of air pollutants.

Spatial Correlation of Industrial NOx Emission in China’s 2 + 26 Policy Region: Based on Social Network Analysis

The Chinese government has identified air pollution transmission points in Beijing–Tianjin–Hebei region and its surrounding areas under 2 + 26 initiative. This study introduces a modified Gravity Model to construct the spatial correlation network of industrial NOx in 2 + 26 policy region from 2011 to 2015, and further explores network characteristics and socioeconomic factors of this spatial correlation network by Social Network Analysis. Results indicate significant correlation of industrial NOx emission in 2 + 26 policy cities. The spatial correlation network of industrial NOx has remained stable within 5 years, implying no pollution exacerbation of interregional transmission. According to the effect of output and input in the correlation network of industrial NOx, cities in 2 + 26 policy region can be categorized into four types: high-high, high-low, low-low, and low-high, as each should adopt the corresponding strategies for emission reduction. Shijiazhuang, Liaocheng, Cangzhou, Heze and Handan should be key monitored during implementation of emission reduction. Taiyuan, Hebi, Langfang, Tangshan and Yangquan, should give priority to local emission reduction although less associated with other cities, based on city type and current emission situation. Environmental regulation and geographical distance have significant influence on the spatial correlation network of industrial NOx, of which the indicator of environmental regulation difference matrix has become significantly negative since 2014, while the indicator of geographical effect has been significantly positive all along. Urban industrial emission has significant correlation between cities with distance of 0–300 km, while no significant correlation between cities with distance exceeding 300 km.

Spatially differentiated effects of socioeconomic factors on China's NOx generation from energy consumption: implications for mitigation policy

Nitrogen oxides (NO_x) has become the priority of China's air pollution control, but the regional socio-economic factors responsible for NO_x generation are embedded with spatial disparities, which leads to different effects of air quality policy at the local level. This study applied a geographically weighted regression (GWR) model to investigate the drivers of NO_x generation from energy consumption (NGEC) in China's 30 provinces, to explore nonstationary spatial effects of NGEC. The results showed that population size has always been the dominant factor in spatial NGEC across all regions of China, although there is a minor north-south difference. However, the effect of per capita GDP and energy intensity leads to a significant north-south difference when they are influencing NGEC, which shows a minor west-east difference from thermal power generation (TE). We also found that in Northern and Northeast China, the transition towards cleaner energy structure based on natural gas has started correlating significantly with NO_x generation through a weakly negative effect in 2015. Our findings show alternative strategies on NO_x reduction, which include the spatially differentiated effect of regional socioeconomic factors on energy consumption.

Quantifying the Impacts of Economic Progress, Economic Structure, Urbanization Process, and Number of Vehicles on PM2.5 Concentration: A Provincial Panel Data Model Analysis of China

With the rapid development of China’s economy, the environmental problems are becoming increasingly prominent, especially the PM_2.5 (particulate matter with diameter smaller than 2.5 μm) concentrations that have exerted adverse influences on human health. Considering the fact that PM_2.5 concentrations are mainly caused by anthropogenic activities, this paper selected economic growth, economic structure, urbanization, and the number of civil vehicles as the primary factors and then explored the nexus between those variables and PM_2.5 concentrations by employing a panel data model for 31 Chinese provinces. The estimated model showed that: (1) the coefficients of the variables for provinces located in North, Central, and East China were larger than that of other provinces; (2) GDP per capita made the largest contribution to PM_2.5 concentrations, while the number of civil vehicles made the least contribution; and (3) the higher the development level of a factor, the greater the contribution it makes to PM_2.5 concentrations. It was also found that a bi-directional Granger causal nexus exists between PM_2.5 concentrations and economic progress as well as between PM_2.5 concentrations and the urbanization process for all provinces. Policy recommendations were finally obtained through empirical discussions, which include that provincial governments should adjust the economic and industrial development patterns, restrict immigration to intensive urban areas, decrease the successful proportion of vehicle licenses, and promote electric vehicles as a substitute to petrol vehicles.

The Spatial–Temporal Variation of Tropospheric NO2 over China during 2005 to 2018

In recent years, new and strict air quality regulations have been implemented in China. Therefore, it is of great significance to evaluate the current air pollution situation and effectiveness of actions. In this study, Ozone Monitoring Instrument (OMI) satellite data were used to detect the spatiotemporal characteristics of tropospheric NO2 columns over China from 2005 to 2018, including spatial distribution, seasonal cycles and long-term trends. The averaged NO2 pollution is higher in southeastern China and lower in the northwest, which are well delineated by the Heihe–Tengchong line. Furthermore, the NO2 loadings are highest in the North China Plain, with vertical column density (VCD) exceeding 13 × 1015 molec cm−2. Regarding the seasonal cycle, the NO2 loadings in eastern China is highest in winter and lowest in summer, while the western region shows the opposite feature. The amplitude of annual range increase gradually from the south to the north. If the entire period of 2005–2018 is taken into account, China has experienced little change in NO2. In fact, however, there appears to be significant trends of an increase followed by a downward tendency, with the turning point in the year 2012. In the former episode of 2005–2012, increasing trends overwhelm nearly the whole nation, especially in the Jing–Jin–Tang region, Shandong Province, and Northern Henan and Southern Hebei combined regions, where the rising rates were as high as 1.0–1.8 × 1015 molec cm−2 year−1. In contrast, the latter episode of 2013–2018 features remarkable declines in NO2 columns over China. Particularly, the regions where the decreased degree was remarkable in 2013–2018 were consistent with the regions where the upward trend was obvious in 2005–2012. Overall, this upward–downward pattern is true for most parts of China. However, some of the largest metropolises, such as Beijing, Shanghai and Guangzhou, witnessed a continuous decrease in the NO2 amounts, indicating earlier and more stringent measures adopted in these areas. Finally, it can be concluded that China’s recent efforts to cut NO2 pollution are successful, especially in mega cities.

Overview on the spatial-temporal characteristics of the ozone formation regime in China

Ozone (O3), a main component in photochemical smog, is a secondary pollutant formed through complex photochemical reactions involving nitrogen oxides (NOx) and volatile organic compounds (VOCs). In the past few decades, with the rapid economic development, industrialization and urbanization, the mixing ratio of O3 has increased substantially in China. O3 non-attainment days have been frequently observed. Despite great efforts made in the past few years, it is still difficult to alleviate O3 pollution in China, due to its non-linear relationship with the precursors. In view of the severe situation in China, this study presents a comprehensive review on the spatial-temporal variations of the relationship between O3 and its precursors (i.e. O3 formation regime), built upon the previous reviews of the spatial-temporal variations of O3 and its precursor levels. Valuable findings from previous studies are laid out for a better understanding of O3 pollution, followed by implications for the control of O3 pollution. This literature review indicates that O3 formation in most areas of the North China Plain (NCP), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions is in a VOC-limited regime during the high-O3 seasons due to dramatic emissions from human activities in cities. Outside these metropolitan areas, a NOx-limited regime dominates rural/remote areas. From summer to winter, the O3 formation regime over China shows a tendency to shift to a VOC-limited regime. Furthermore, O3 formation in China shifted toward increasing sensitivity to VOC emissions before the 12th Five-Year-Plan. However, after the 12th Five-Year-Plan, successful reduction of NOx slowed down this trend. Further effective control of VOCs is expected to achieve sustained O3 attainment in the future. To timely solve the current O3 pollution problem, precise control of O3 precursors is proposed, together with the joint prevention and control of regional air pollution.

Simulation-Based Assessment of Multilane Separate Freeways at Toll Station Area: A Case Study from Huludao Toll Station on Shenshan Freeway

To support the rapid growth of demand in passengers and freight, separating trucks and passenger-cars is a potential solution to improve traffic efficiency and safety. The primary purpose of this paper is to comprehensively assess the multilane separate freeway at Huludao Toll Station in Liaoning Province, China. Based on the configuration and segmentation of the freeway near a toll station, a six-step guidance strategy is designed to adapt to the separate organization mode. Five conventional traffic scenarios are designed in the Vissim platform for comparative analysis between different guidance strategies. To investigate the vehicle-to-infrastructure (V2I) environment, a microscopic testbed is established with cooperative car-following and lane-changing models using the MATLAB platform. The numerical simulation results show that the guidance strategy significantly improves efficiency and safety, and also reduces emissions and fuel consumption. Meanwhile, pre-guidance before toll channels outperforms the scenario only applied with guidance measures after toll plaza. Compared to conventional conditions, the assessment of pollutant emissions and fuel consumption also embodies the superiority of the other five scenarios, especially in the sections of toll plaza and channels with the lowest efficiency and safety level. Generally, all indexes indicate that the cooperative V2I technology is the best alternative for multilane separate freeways.

The Spatial and Heterogeneity Impacts of Population Urbanization on Fine Particulate (PM2.5) in the Yangtze River Economic Belt, China

This paper addresses the effect of population urbanization on Fine Particulate (PM2.5) in the Yangtze River Economic Belt in China from 2006 to 2016 by employing PM2.5 remote sensing data and using the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. The study contributes to the growing empirical literature by addressing heterogeneity, spillover, and dynamic effects in the dynamic spatial panel modeling process simultaneously. The empirical results show that population urbanization has a significant impact on PM2.5 with a positive spillover effect and a dynamic effect being detected and controlled. The heterogeneity effects of population urbanization on PM2.5 due to geographical positions show evidence of an obvious inverted U-shaped curve relationship in the upstream area and an increasing function curve in the midstream and downstream areas. The heterogeneity effects due to population urbanization levels show that an inverted N-shape curve relationship exists in low and medium urbanization level areas, while a U-shape curve relationship exists in high urbanization level areas. It is hoped that this study will inform the local governments about the heterogeneity of population urbanization and spillover effects of air pollution when addressing air pollution control.

A Spatio-Temporal Pattern and Socio-Economic Factors Analysis of Improved Sanitation in China, 2006⁻2015

Ensuring an adequate and safe access to sanitation is essential to prevent diseases. Using provincial spatial panel data reported in the China Health Statistical Yearbook and the China Statistical Yearbook, this paper analyzed the spatio-temporal characteristics of improved rural sanitation in 30 Chinese provinces during the period 2006⁻2015, and analyzed factors that may affect improved sanitation rates in rural China. Spatial autocorrelations of improved sanitation rates were computed via Global and Local Moran's I firstly, and then, inter-provincial disparities of improved sanitation were assessed by using the Theil index estimator; finally, the spatial panel model was employed to examine the potential socio-economic factors. Spatial autocorrelations results suggested that the provincial improved sanitation rates changes affect both the provinces themselves and the adjacent regions; Analysis of the spatial panel model revealed that factors such as GDP per capita, investment proportion ratio, centralized water supply, rural residents' expenditure were positively associated with improved sanitation rates, and illiteracy rate of people older than 15 was negatively related with improved sanitation rates. Socio-economic factors had affected the improved sanitation rates in 30 provinces in rural China. Thus, a series of policies, socio-economic measures and personal latrine literacy education should be given to improve the status of improved sanitation rates in rural China.

Short-Term Trend Forecast of Different Traffic Pollutants in Minnesota Based on Spot Velocity Conversion

Because traffic pollution is a global problem, the prediction of traffic emissions and the analysis of their influencing factors is the key to adopting management and control measures to reduce traffic emissions. Hence, the evaluation of the actual level of traffic emissions has gained more interest. The Computer Program to calculate Emissions from Road Transport model (COPERT) is being downloaded by 100 users per month and is being used in a large number of applications. This paper uses this model to calculate short-term vehicle emissions. The difference from the traditional research was that the input velocity parameter was not the empirical value, but through reasonable conversion of the spot velocity at one point, obtained by the roadside detector, which provided new ideas for predicting traffic emissions by the COPERT model. The hybrid Autoregressive Integrated Moving Average (ARIMA) Model was used to predict spot mean velocity, after converted it to the predicted interval velocity averaged for some period, input the conversion results and other parameters into the COPERT IV model to forecast short-term vehicle emissions. Six common emissions (CO, NO_X, CO₂, SO₂, PM₁₀, NMVOC) of four types of vehicles (PC, LDV, HDV, BUS) were discussed. As a result, PM₁₀ emission estimates increased sharply during late peak hours (from 15:30 p.m.⁻18:00 p.m.), HDV contributed most of NO_X and SO₂, accounting for 39% and 45% respectively. Based on this prediction method, the average traffic emissions on the freeway reached a minimum when interval mean velocity reduced to 40 km/h⁻60 km/h. This paper establishes a bridge between the emissions and velocity of traffic flow and provides new ideas for forecasting traffic emissions. It is further inferred that the implementation of dynamic velocity guidance and vehicle differential management has a controlling effect that improves on road traffic pollution emissions.