Average Annual Concentrations Of PM2 Research Articles

Multi-Year Continuous Observations of Ambient PM2.5 at Six Sites in Akure, Southwestern Nigeria

The spatial–temporal variations of fine particulate matter (PM2.5) in Akure, a city in southwestern Nigeria, are examined based on multi-year continuous observations using low-cost PM2.5 sensors at six different sites. The average annual concentration of PM2.5 across these sites was measured at 41.0 µg/m3, which surpassed both the Nigerian national air quality standard and the World Health Organization air quality guideline level. PM2.5 levels were significantly higher during the dry season (November–March), often exceeding hazardous levels (over 350 µg/m3), than during the wet season. The analyses of trends in air mass trajectories and satellite data on fire occurrences imply that the transport of dust and accumulation of PM2.5 originating from local/regional open burning activities played crucial roles in increased PM2.5 concentrations during the dry season. Further, site-to-site variations in the PM2.5 levels were observed, with relatively high concentrations at less urbanized sites, likely due to high local emissions from solid fuel combustion, waste burning, and unpaved road dust. Diurnal patterns showed morning and evening peaks at less urbanized sites, accounting for an estimated 51–77% of local emissions. These results highlight the importance of local emission sources in driving spatial–temporal PM2.5 variations within the city and the need for targeted mitigation strategies to address the significant air pollution challenges in Akure and similar regional cities in West Africa.

Exploring the Burden of PM2.5-Related Deaths and Economic Health Losses in Beijing.

Air pollution is one of the major global public health challenges. Using annual fine particulate matter (PM2.5) concentration data from 2016 to 2021, along with the global exposure mortality model (GEMM), we estimated the multi-year PM2.5-pollution-related deaths divided by different age groups and diseases. Then, using the VSL (value of statistical life) method, we assessed corresponding economic losses and values. The number of deaths attributed to PM2.5 in Beijing in 2021 fell by 33.74 percent from 2016, while health economic losses would increase by USD 4.4 billion as per capita disposable income increases year by year. In 2021, the average annual concentration of PM2.5 in half of Beijing's municipal administrative districts is less than China's secondary ambient air quality standard (35 μg/m3), but it can still cause 48,969 deaths and corresponding health and economic losses of USD 16.31 billion, equivalent to 7.9 percent of Beijing's GDP. Therefore, it is suggested that more stringent local air quality standards should be designated to protect public health in Beijing.

The Role of Energy Policies for Air Pollution Control in the Po Valley

This paper examines the use of integrated assessment modelling to select policies aimed at reducing air pollution in response to growing concerns about the deterioration of air quality, especially in highly populated and industrialized areas. The study focuses on the Po Valley region in northern Italy, renowned for its intricate environmental difficulties arising from industrial operations, extensive farming, and topographic characteristics. The goal of the multi-objective decision problem is to find the best plans for reducing emissions that will minimize the average annual concentrations of PM2.5 while also considering the costs of putting these plans into action and incorporating end-of-pipe, energy, and fuel switch measures. Results highlight the trade-offs between air quality improvement and associated costs, presenting a Pareto curve of optimal solutions.

Association between long-term PM2.5 exposure and risk of Kawasaki disease in children: A nationwide longitudinal cohort study

BackgroundBased on previous studies suggesting air pollution as a potential risk factor for Kawasaki Disease (KD), we examined the association of long-term exposure to childhood fine particulate matter (PM2.5) with the risk of KD. MethodsWe used National Health Insurance Service–National Sample Cohort data from 2002 to 2019, which included beneficiaries aged 0 years at enrollment and followed-up until the onset of KD or age 5 years. The onset of KD was defined as the first hospital visit record with a primary diagnostic code of M30.3, based on the 10th revision of the International Classification of Diseases, and with an intravenous immunoglobulin (IVIG) prescription. We assigned PM2.5 concentrations to 226 districts, based on mean annual predictions from a machine learning-based ensemble prediction model. We performed Cox proportional-hazards modeling with time-varying exposures and confounders. ResultsWe identified 134,634 individuals aged five or less at enrollment and, of these, 1220 individuals who had a KD onset and an IVIG prescription during study period. The average annual concentration of PM2.5 exposed to the entire cohort was 28.2 μg/m³ (Standard Deviation 2.9). For each 5 μg/m³ increase in annual PM2.5 concentration, the hazard ratio of KD was 1.21 (95% CI 1.05–1.39). ConclusionsIn this nationwide, population-based, cohort study, long-term childhood exposure to PM2.5 was associated with an increased incidence of KD in children. The study highlights plausible mechanisms for the association between PM2.5 and KD, but further studies are needed to confirm our findings.

Lung cancer cases attributable to PM2.5 in northeastern Italy

Abstract Background According to the International Agency for Cancer Research (IARC), outdoor pollution is a well established cause of lung cancer, with a prominent carcinogenic role attributed to particulate matter (PM) pollution. 2001 WHO guidelines on outdoor pollution includes a recommendation to reach a PM2.5 annual average of 5ug/m3. The WHO recommendation is in sharp contrast with EU limits: thus, in the present study we estimated the number of incident lung cancer cases due to PM2.5 according to three different scenarios. Methods The number of newly incident lung cancer cases diagnosed in northeastern Italy from 2015 to 2020 was from the population-based cancer registry of the Friuli Venezia Giulia region. We considered three scenarios of average annual concentration of PM2.5: 25ug/m3 according to EU legislation; 10ug/m3 or 5ug/m3 according to 2005 and 2021 WHO guidelines. An 8% increase in the risk of lung cancer for every 10ug/m3 increase in PM2.5 was assumed. Data from outdoor average annual concentration of PM2.5 in northeastern Italy were from local air monitoring systems. Results 5131 lung cancer cases were registered in 2015-2020 in Friuli Venezia Giulia, (i.e., 855 cases/year). In the same period, an average annual concentration of PM2.5 of 18ug/m3 was documented. According to EU legislation, there will not be an excess of future lung cancer cases attributable to PM2.5. Conversely, the projection of the excess cases ranged from 6.4%/year (WHO 2005) or 10.4% (WHO 2021). In absolute terms, we estimated that there will be an excess of future yearly lung cancer cases ranging from 55 cases to 89 cases due to PM2.5.air pollution exceeding WHO recommendations. Conclusions According to WHO recommendations, PM2.5 air pollution will cause an excess of up to 89 yearly cases of lung cancer in Friuli Venezia Giulia, northeastern Italy, a projection in sharp contrast with EU limits. Key messages • An excess of up to 89 yearly cases of lung cancer are projected for the future years due to PM2.5 concentration exceeding WHO guidelines. • EU limits of PM2.5 average yearly concentration underestimate the risk of lung cancer in humans.

Associations of neighbourhood environmental attributes and socio-economic status with health-related quality of life in urban mid-aged and older adults: Mediation by physical activity and sedentary behaviour

This study examined the associations of objectively assessed physical features of the neighbourhood environment with physical and mental aspects of health-related quality of life (HRQoL) as measured by the SF-36, and the roles of physical activity and sedentary behaviour in these associations. We used data from a national sample of Australian mid-aged and older adults living in urban areas (N = 4141). Environmental attributes were computed for 1-km-radius areas surrounding participants' residential addresses. Neighbourhood socio-economic status (SES) and average annual concentrations of PM2.5 were the only attributes related to HRQoL in the expected direction in the total- and direct-effect regression models. All other environmental attributes were related to HRQoL via physical activity behaviours and leisure-time sitting. The associations of most environmental features with HRQoL mediated by physical activity and sedentary behaviours were inconsistent, positive through some pathways and negative through others. This study suggests that neighbourhood SES may in part benefit HRQoL by helping promote an active lifestyle. Neighbourhood attributes defining walkability may benefit HRQoL by providing opportunities for walking and resistance training and, through these, by helping reduce leisure-time sitting. However, the same attributes also may limit opportunities for household activities and gardening and negatively impact on HRQoL through these pathways.

Statistical Characteristics of Monthly Mean and Annual Concentrations of Particulate Matter PM2.5 and PM10 in Three Points of Tbilisi in 2017-2022

Results of the detailed statistical analysis of the average monthly and annual concentrations of particulate matter PM2.5 and PM10 at three locations in Tbilisi (Kazbegi av., Tsereteli av. and Varketili) in 2017-2022 are presented. An analysis of the correlations between the indicated characteristics of air pollution has been carried out. The variability of the average annual values of PM2.5 and PM10 in the study period of observations was studied. In particular, it was found that in 2020-2021 there was a significant decrease in the average annual concentration of aerosols due to restrictions on the movement of vehicles associated with the covid-19 pandemic. It is noted that for the entire observation period, the average annual concentration of PM2.5 and PM10 was above the permissible norm.

Does air pollution affect traffic safety? Evidence from cities in China.

Does air pollution influence traffic safety? To answer this question, this paper empirically investigates the nonlinear impact of air pollution on traffic mortality by employing a balanced panel dataset for 102 Chinese cities covering 2014-2018. Also, this paper then discusses the nonlinear mediation effects of air pollution on traffic safety to test the influential mechanism between these two variables. The following three conclusions are obtained. First, air pollution has a nonlinear impact on traffic safety: a 1μg/m3 increase in the average annual concentration of PM2.5 could lead to a 0.0439 increase in traffic fatalities per one million people, but the negative impact of PM2.5 on air pollution will be reduced in the long run. Second, heterogeneity analysis indicates that the impact of air pollution on traffic safety in northern cities of China, cities with lower levels of economic development is more serious than that in other cities. Third, air pollution may affect traffic safety by reducing transport efficiency and affecting drivers' physiological status and cognitive abilities.

New-type urbanization efficiency measurement in Shanghai under the background of industry city integration.

With the development of urbanization, the problem of the disintegrated between industry and city became more prominent, exploring the reasons. The efficiency of new-type industry has been the crucial factor in city-industry integration. This paper constructs the measurement index system of new-type urbanization via DEA-BCC methodology, starting from the quality of urbanization to analyze the efficiency of urbanization. This paper chooses the total energy consumption, general public budget expenditure, and the proportion of employment personnel in the tertiary industry in all urban units as input variables. The total retail sales of consumer goods, urbanization rate, average annual concentration of pm2.5 (popW), and built-up area as output variables. This paper uses DEA method to measure the comprehensive efficiency value, technical efficiency value, and scale efficiency value of new urbanization in Shanghai, and analyzes the influencing factors of urbanization efficiency. The results show the following: (1) The overall level of comprehensive efficiency value, technical efficiency value, and scale efficiency of Shanghai's new-type urbanization are relatively high, especially the technical efficiency basically stays at a high level. The overall trend of scale efficiency and comprehensive efficiency is consistent, and the comprehensive efficiency is greatly influenced by scale efficiency. (2) The technical efficiency of urbanization in Shanghai is close to the optimal, and there is little space for further increasing technological input to improve the comprehensive efficiency of new-type urbanization. The scale efficiency is slightly lower than the technical efficiency, and there is still some space for optimization. (3) In terms of urbanization input indicators, Shanghai's total energy consumption and general public budget input were too much in the early years, which led to the reduction of urbanization efficiency, and the situation has been improved in recent years. In terms of the output index of urbanization, increasing the total retail sales of social consumer goods and the output of built-up area can make the urbanization efficiency of Shanghai reach the optimal efficiency.

The effect of fine suspended particles in the atmospheric air on the formation and course of the T2 endotype of bronchial asthma: a case-control study

The aim of the study was to investigate the effect of fine suspended particles in the atmospheric air on the formation and course of allergic and non-allergic phenotypes of the T2 endotype of bronchial asthma (BA) using the case-control study. Materials and methods. BA patients were selected in the course of seeking medical help. The groups were formed on the base of matching criteria (gender, age, body mass index, level of education), supplemented by the collection of information about potential cofounders. Based on the data on monitoring the content of fine suspended particles in the atmospheric air of Kazan, the average annual and maximum concentrations of PM2.5 and PM10 fractions were determined in the residential areas. The group of “cases” included forty patients with an allergic phenotype and 42 patients with an eosinophilic non-allergic phenotype of bronchial asthma, the control group included forty eight people. Additionally, sampling of atmospheric air was carried out using an 8-stage impactor to assess the content of bacterial endotoxin, and elemental composition. Results. Higher levels of pollution with fine suspended particles were demonstrated in the areas of residence of BA patients, comparing to the control group. An increase in the average annual concentration of the PM2.5 by 10 µg/m3 increases the odds of the eosinophilic non-allergic BA phenotype in adults by 4.76 times. The odds of the allergic phenotype of bronchial asthma increases in the presence of bacterial endotoxin - 1.32 times per 0.01 EU/m3 of endotoxin in the 3.2-18 µm size fraction. A more severe course of the eosinophilic non-allergic BA phenotype was noted at higher average annual concentrations of the PM2.5. The control of allergic asthma depends on the bacterial contamination of the aerosol. Limitations of the study are related to the use of geospatial approach to assess personalized average annual and maximum annual concentrations. Conclusion. The role of fine suspended particles in the atmospheric air in the development of bronchial asthma in adults has been shown. Various mechanisms were established to be involved in the formation of the clinical picture of the eosinophilic non-allergic and allergic phenotypes of bronchial asthma.

Modeling of reducing NH4NO3 in PM2.5 under high ammonia emission in urban areas: Based on high-resolution data

At present, the air quality in urban areas in China has continued to improve, but PM2.5 is still severely polluted in autumn and winter and is difficult to meet the Chinese standard. With the renovation of coal-fired boilers and the transformation of ultra-low emissions in factories, NO3− has gradually become the main inducing species for high levels of PM2.5. In this study, a high-resolution (1 h) online instrument was used to analyze the characteristics of atmospheric PM2.5 in the autumn and winter periods from October 2019 to February 2020 at Zhengzhou University in Zhengzhou. The inorganic nitrate in PM2.5 mainly existed in the form of semivolatile NH4NO3, and the method of reducing NH4NO3 was studied through data analysis. The basic method of reducing particulate nitrate in PM2.5 is not only to reduce nitrate precursors (NOx) but also to transform particulate nitrate into gas by reducing the aerosol pH value (enhancing aerosol acidity). The simulation analysis of NHx (NHx = NH3+NH4+), NO3T (NO3T=HNO3+NO3−), and SO42− reduction using the thermodynamic model ISORROPIA-II revealed that total ammonia (TA) has an obvious peak clipping effect on particulate NO3− when it is reduced by 60% and can effectively reduce NH4NO3 in PM2.5. The reliability and credibility of the data results were enhanced through long-term observation and local time analysis, and reducing TA and NO3− in areas with high ammonia emissions was proven to be feasible. This study is beneficial for formulating measures to reduce the average annual concentration of PM2.5 in ammonia-rich areas.

大气污染规制对城市空气污染的防治成效——基于准实验分析

PDF HTML阅读 XML下载 导出引用 引用提醒 大气污染规制对城市空气污染的防治成效——基于准实验分析 DOI: 10.5846/stxb202107262020 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（72033005）；中国博士后科学基金项目（2021M701507）；教育部人文社会科学研究项目（20YJC790014）；江西省教育厅科技项目（GJJ200534） The Effect of air pollution regulation on urban air pollution prevention and control: Evidence from a Quasi-Natural Experiment Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:以2003年实施的大气污染防治重点城市政策为准自然实验，运用双重差分模型从区域层面分析了大气污染规制对城市空气污染治理的影响，研究发现：（1）大气污染规制在1%的显著性水平下降低了重点城市的工业二氧化硫排放强度，工业二氧化硫排放量以及城市PM2.5年均浓度值。（2）大气污染防治重点城市政策实施后的9年时间内有效减少了12215.8万t城市工业二氧化硫排放量，并且使得城市PM2.5年均浓度改善2.97μg/m3，下降比分别达到了36.2%和8.5%，平均每年减少了3.7%的城市工业二氧化硫排放量并降低0.944%的城市PM2.5浓度值。（3）大气污染防治重点城市政策对于城市空气污染治理主要是通过减少能源消耗量、增加城市污染治理力度、促进规制地区产业结构转型升级和提升生产技术水平等渠道予以实现。 Abstract:Based on the quasi-natural experiment of the key city policy of air pollution control implemented in 2003, this paper analyzes the impact of air pollution regulation on urban air pollution control from the regional level by using Differences-in-Difference model. The results show that:(1) air pollution regulation significantly reduce the intensity of industrial sulfur dioxide emission, industrial sulfur dioxide emission and PM2.5 annual concentration in key cities. (2) In the nine years after the implementation of the policy, 122.158 million tons of urban industrial sulfur dioxide emissions have been effectively reduced, and the average annual concentration of PM2.5 has been improved by 2.97 μg/m3, with the reduction ratio of 36.2% and 8.5% respectively. The average annual sulfur dioxide emission of urban industry has been reduced by 3.7% and the urban PM2.5 concentration has been reduced by 0.944%. (3) The key city policy of air pollution prevention and control for urban air pollution control is mainly realized by reducing energy consumption, increasing the intensity of urban pollution control, promoting the transformation and upgrading of regional industrial structure and improving the level of production technology. 参考文献 相似文献 引证文献

Estimation of long-term and short-term health effects attributed to PM2.5 standard pollutants in the air of Ardabil (using Air Q + model).

Clean air is considered as a basic need for human health. However, air pollution is a significant threat to health in developed and developing countries. The aim of this study was to estimate the health effects attributed to PM2.5 pollutants in the air of Ardabil in 2018 (using Air Q + model). Raw data related to particles were collected from the Department of Environment and processed in Excel software and converted into an input file of the Air Q + model, and in the final stage, by considering appropriate epidemiological parameters and combining these data with air quality data, it was possible to estimate the health effects of air pollution. The results showed that the average annual concentrations of PM2.5 and PM10 were 15.47 and 30.94 in the study year, respectively. The total number of deaths due to ALRI, COPD, lung cancer, IHD, and stroke deaths on average during the study period were estimated to be 73, 11, 7, 15, and 14 deaths, respectively, which include 14.62, 15.78, 4.9, 12.43, and 11.6% of deaths due to ALRI, COPD, lung cancer, IHD, and stroke deaths, respectively. In conditions of concentration above 5µg/m3, attributed proportion, total number of attributed cases and number of attributed cases per 100,000 population (with moderate relative risk and confidence interval of 95%) for cardiovascular diseases have been estimated to be 0.95% 103 people and 42.19 people. Also, the attributed proportion, the total number of attributable cases, and the number of attributable cases per 100,000 population (with moderate relative risk and confidence of 95%) for the admission of respiratory diseases have been estimated at 97.1%, 68 persons and 3 persons, respectively. Our results suggest that particle exposure even at low concentrations is associated with an increased risk of overall mortality and specific cause mortality and hospital admissions for respiratory and cardiovascular diseases.

Does Low-Carbon City Pilot Policy Alleviate Urban Haze Pollution? Empirical Evidence from a Quasi-Natural Experiment in China.

As a comprehensive environmental regulation, the low-carbon city pilot policy (LCCP) may have an impact on haze pollution. The evaluation of the effectiveness of LCCP on haze pollution is greatly significant for air pollution prevention and control. Taking LCCP as the starting point, in this study we constructed DID, PSM-DID, and intermediary effect models to empirically test the impact and mechanism of LCCP on haze pollution, based on the panel data of 271 cities in China from 2005 to 2018. The findings show that (1) LCCP has significantly reduced the urban haze pollution, and the average annual concentration of PM2.5 in pilot cities decreased by 14.29%. (2) LCCP can inhibit haze pollution by promoting technological innovation, upgrading the industrial structure, and reducing energy consumption. Among these impacts, the effect of technological innovation is the strongest, followed by industrial structure, and energy consumption. (3) LCCP has significantly curbed the haze pollution of non-resource dependent cities, Eastern cities, and large cities, but exerted little impact on resource-dependent cities, Central and Western regions, and small and medium-sized cities. (4) LCCP has a spatial spillover effect. It can inhibit the haze pollution of adjacent cities through demonstration and warning effects. This study enriches the relevant research on LCCP and provides empirical support and policy enlightenment for pollution reduction.

Source Apportionment and Health Risk Assessment of Heavy Metals in PM2.5 in Handan: A Typical Heavily Polluted City in North China

In order to determine the pollution sources and human health risks of metal elements in PM2.5, samples were collected by a large flow particulate matter sampler in the four seasons in 2013, 2015, and 2017 (January, April, July, and October). The mass concentrations of 10 metals (Ti, V, Cr, Mn, Ni, Cu, Zn, As, Cd, and Pb) were analyzed. The sources of heavy metals were identified by Unmix, and the potential non-carcinogenic/carcinogenic risk was evaluated. The influences of local and regional sources were also explored during the high-carcinogenic risk period (HCRP). The wind field and 72 h backward trajectories were performed to identify the potential local and regional sources in HCRP. The results showed that the average annual concentrations of PM2.5 in the urban area of Handan city were 105.14, 91.18, and 65.85 μg/m3 in 2013, 2015, and 2017, respectively. The average daily concentrations of the metals in PM2.5 in January were higher than that of April, July, and October. The average mass concentrations of the 10 heavy metal elements in PM2.5 were 698.26, 486.92, and 456.94 ng·m−3 in 2013, 2015, and 2017, respectively. The main sources of the metals in PM2.5 were soil dust sources, vehicular emissions, coal burning, and industrial activities. The carcinogenic risks of Cr and As were above 1 × 10−6 over the three years. Wind direction analysis showed that the potential local sources were heavy industry enterprises and the economic development zone. The backward trajectory analysis indicated that PM2.5 long transported from Shandong, Henan, and the surrounding cities of Handan had quite an impact on the heavy metals contained in the atmosphere of the studied area. The health risk assessment results demonstrated that the trend for non-carcinogenic risk declined, and there was no non-carcinogenic risk in 2017. However, the carcinogenic risk levels were high over the three years, particularly in January.

Estimation of PM<sub>2.5</sub> concentration in China using linear hybrid machine learning model

Abstract. Satellite remote sensing aerosol optical depth (AOD) and meteorological elements were employed to invert PM2.5 (the fine particulate matter with a diameter below 2.5 µm) in order to control air pollution more effectively. This paper proposes a restricted gradient-descent linear hybrid machine learning model (RGD-LHMLM) by integrating a random forest (RF), a gradient boosting regression tree (GBRT), and a deep neural network (DNN) to estimate the concentration of PM2.5 in China in 2019. The research data included Himawari-8 AOD with high spatiotemporal resolution, ERA5 meteorological data, and geographic information. The results showed that, in the hybrid model developed by linear fitting, the DNN accounted for the largest proportion, and the weight coefficient was 0.62. The R2 values of RF, GBRT, and DNN were reported as 0.79, 0.81, and 0.8, respectively. Preferably, the generalization ability of the mixed model was better than that of each sub-model, and R2 (determination coefficient) reached 0.84, and RMSE (root mean square error) and MAE (mean absolute error) were reported as 12.92 and 8.01 µg m−3, respectively. For the RGD-LHMLM, R2 was above 0.7 in more than 70 % of the sites and RMSE and MAE were below 20 and 15 µg m−3, respectively, in more than 70 % of the sites due to the correlation coefficient having a seasonal difference between the meteorological factor and PM2.5. Furthermore, the hybrid model performed best in winter (mean R2 was 0.84) and worst in summer (mean R2 was 0.71). The spatiotemporal distribution characteristics of PM2.5 in China were then estimated and analyzed. According to the results, there was severe pollution in winter with an average concentration of PM2.5 being reported as 62.10 µg m−3. However, there was only slight pollution in summer with an average concentration of PM2.5 being reported as 47.39 µg m−3. The period from 10:00 to 15:00 LT (Beijing time, UTC+8 every day is the best time for model inversion; at this time the pollution is also high. The findings also indicate that North China and East China are more polluted than other areas, and their average annual concentration of PM2.5 was reported as 82.68 µg m−3. Moreover, there was relatively low pollution in Inner Mongolia, Qinghai, and Tibet, for their average PM2.5 concentrations were reported below 40 µg m−3.

Spatial Spillover Effects of Air Pollution on the Health Expenditure of Rural Residents: Based on Spatial Durbin Model.

Background: Air pollution is one source of harm to the health of residents, and the impact of air pollution on health expenditure has become a hot topic worldwide. However, few studies aim at the spatial spillover effects of air pollution on the health expenditure of rural residents (HE-RR), including the impact on the health expenditure in neighboring areas. Objective: Based on the existing research, this paper further introduces the spatial dimension and uses the Spatial Durbin model to discuss the impact of environmental pollution on the health expenditure of rural residents (HE-RR). Methods: Based on provincial panel data during 2002–2015 in China, the Spatial Durbin model was used to investigate the spatial spillover effect of the average annual concentration of PM2.5 (AAC-PM2.5) on the health expenditure of rural residents (HE-RR). Results: There was a significant positive correlation between AAC-PM2.5 and health expenditure of rural residents (HE-RR) in neighboring areas at a significant level of 5% (COEF: 2.546, Z: 2.340), that is, AAC-PM2.5 has a spatial spillover effect on PC-HE-RR in neighboring areas, and the spatial spillover effect is greater than the direct effect. The migration and diffusion of PM2.5 pollution will affect the air quality of neighboring areas, leading to the health risk not only from the local PM2.5 pollution but also the nearby PM2.5 pollution. Conclusion: The results show a significant positive relationship between air pollution and HE-RR in neighboring areas, and the spatial spillover effect is greater than the direct effect.

Effectiveness of SOx, NOx, and Primary Particulate Matter Control Strategies in the Improvement of Ambient PM Concentration in Taiwan

The Community Multiscale Air Quality (CMAQ) measurement was employed for evaluating the effectiveness of fine particulate matter control strategies in Taiwan. There are three scenarios as follows: (I) the 2014 baseline year emission, (II) 2020 emissions reduced via the Clean Air Act (CAA), and (III) other emissions reduced stringently via the Clean Air Act. Based on the Taiwan Emission Data System (TEDs) 8.1, established in 2014, the emission of particulate matter 2.5 (PM2.5) was 73.5 thousand tons y−1, that of SOx was 121.3 thousand tons y−1, and that of NOx was 404.4 thousand tons y−1 in Taiwan. The CMAQ model simulation indicated that the PM2.5 concentration was 21.9 μg m−3. This could be underestimated by 24% in comparison with data from the ambient air quality monitoring stations of the Taiwan Environmental Protection Administration (TEPA). The results of the simulation of the PM2.5 concentration showed high PM2.5 concentrations in central and southwestern Taiwan, especially in Taichung and Kaohsiung. Compared to scenario I, the average annual concentrations of PM2.5 for scenario II and scenario III showed reductions of 20.1% and 28.8%, respectively. From the results derived from the simulation, it can be seen that control of NOx emissions may improve daily airborne PM2.5 concentrations in Taiwan significantly and control of directly emitted PM2.5 emissions may improve airborne PM2.5 concentrations each month. Nevertheless, the results reveal that the preliminary control plan could not achievethe air quality standard. Therefore, the efficacy and effectiveness of the control measures must be considered to better reduce emissions in the future.

Evaluating the effect of sample length on forecasting validity of FGM(1,1)

Three indicators (GDP, PCDIIP-rh and Total Population) are selected in this paper to study the effect of sample length on forecasting validity of FGM(1,1). It has passed the test, such as development coefficient, mean relative error within the sample, and ratio of mean square error. The above three sets of indicators are proved to be suitable for FGM(1,1) to make predictions. The results of the study indicate that the forecasting of 4–6 sample lengths is the most appropriate. The MAPE of 5 sample length is better than sample lengths 4 or 6. The conclusion of this study is verified by taking the oil production of India and Canada as examples. On this basis, the sample length 5 is selected to predict the average annual concentration of PM2.5 from 2019 to 2021 in Xingtai. The forecasting results show that the PM2.5 in Xingtai will decline in the next three years, but it will not reach the national level 2 concentration limit.

The effect of forest on PM2.5 concentrations: A spatial panel approach

Spatial relationships between forest and PM2.5 concentrations are of great policy implications in regional afforestation layout and air pollution control. This paper investigates the transboundary externality of a city’s forest on the concentrations of PM2.5 in different city segments. Employing a mixed-regressive spatial panel model with data for 255 Chinese cities over 2000 to 2015, we find that the concentrations of PM2.5 tend to be substantially lower in cities with larger forest area and the depositing effect of forest spills over significantly to neighboring cities. A one percentage increase in forest area reduces the average annual concentrations of PM2.5 by 2.53%, of which 76% is contributed to the spillover effect. Moreover, the average marginal effect of forest on PM2.5 concentrations exhibits an inverted-U relationship with wind speed and the depositing effect minimizes (in magnitude) as the average annual speed of wind approaches to 23 kilometers per hour. These findings suggest that severe hazing cities with mild wind speed are priority afforestation areas for transboundary air pollution control.