Long-term characteristics of satellite-based PM2.5 over East China

Prediction of developmental toxic effects of fine particulate matter (PM2.5) water-soluble components via machine learning through observation of PM2.5 from diverse urban areas

The global health implications of fine particulate matter (PM2.5) underscore the imperative need for research into its toxicity and chemical composition. In this study, zebrafish embryos exposed to the water-soluble components of PM2.5 from two cities (Harbin and Hangzhou) with differences in air quality, underwent microscopic examination to identify primary target organs. The Harbin PM2.5 induced dose-dependent organ malformation in zebrafish, indicating a higher level of toxicity than that of the Hangzhou sample. Harbin PM2.5 led to severe deformities such as pericardial edema and a high mortality rate, while the Hangzhou sample exhibited hepatotoxicity, causing delayed yolk sac absorption. The experimental determination of PM2.5 constituents was followed by the application of four algorithms for predictive toxicological assessment. The random forest algorithm correctly predicted each of the effect classes and showed the best performance, suggesting that zebrafish malformation rates were strongly correlated with water-soluble components of PM2.5. Feature selection identified the water-soluble ions F- and Cl- and metallic elements Al, K, Mn, and Be as potential key components affecting zebrafish development. This study provides new insights into the developmental toxicity of PM2.5 and offers a new approach for predicting and exploring the health effects of PM2.5.

Exploring the Spatiotemporal Evolution and Socioeconomic Determinants of PM2.5 Distribution and Its Hierarchical Management Policies in 366 Chinese Cities

From 2013 to 2017, progress has been made by implementing the Air Pollution Prevention and Control Action Plan. Under the background of the 3 Year Action Plan to Fight Air Pollution (2018–2020), the pollution status of PM2.5, a typical air pollutant, has been the focus of continuous attention. The spatiotemporal specificity of PM2.5 pollution in the Chinese urban atmospheric environment from 2018 to 2020 can be summarized to help conclude and evaluate the phased results of the battle against air pollution, and further, contemplate the governance measures during the period of the 14th Five-Year Plan (2021–2025). Based on PM2.5 data from 2018 to 2020 and taking 366 cities across China as research objects, this study found that PM2.5 pollution has improved year by year from 2018 to 2020, and that the heavily polluted areas were southwest Xinjiang and North China. The number of cities with a PM2.5 concentration in the range of 25–35 μg/m³ increased from 34 in 2018 to 86 in 2019 and 99 in 2020. Moreover, the spatial variation of the PM2.5 gravity center was not significant. Concretely, PM2.5 pollution in 2018 was more serious in the first and fourth quarters, and the shift of the pollution's gravity center from the first quarter to the fourth quarter was small. Global autocorrelation indicated that the space was positively correlated and had strong spatial aggregation. Local Moran's I and Local Geti's G were applied to identify hotspots with a high degree of aggregation. Integrating national population density, hotspots were classified into four areas: the Beijing–Tianjin–Hebei region, the Fenwei Plain, the Yangtze River Delta, and the surrounding areas were selected as the key hotspots for further geographic weighted regression analysis in 2018. The influence degree of each factor on the average annual PM2.5 concentration declined in the following order: (1) the proportion of secondary industry in the GDP, (2) the ownership of civilian vehicles, (3) the annual grain planting area, (4) the annual average population, (5) the urban construction land area, (6) the green space area, and (7) the per capita GDP. Finally, combined with the spatiotemporal distribution of PM2.5, specific suggestions were provided for the classified key hotspots (Areas A, B, and C), to provide preliminary ideas and countermeasures for PM2.5 control in deep-water areas in the 14th Five-Year Plan.

Characteristics and source attribution of PM2.5 during 2016 G20 Summit in Hangzhou: Efficacy of radical measures to reduce source emissions

A field campaign was conducted to study the PM_2.5 and atmospheric gases and aerosol's components to evaluate the efficacy of radical measures implemented by the Chinese government to improve air quality during the 2016 G20 Summit in Hangzhou China. The lower level of PM_2.5 (32.48 ± 11.03 µg/m³) observed during the control period compared to pre-control and post-control periods showed that PM_2.5 was alleviated by control policies. Based on the mass concentrations of particulate components, the emissions of PM_2.5 from local sources including fossil fuel, coal combustion, industry and construction were effectively reduced, but non-exhaust emission was not reduced as effectively as expected. The accumulation of SNA (SO₄^2-, NO₃^-, NH₄⁺) was observed during the control period, due to the favourable synoptic weather conditions for photochemical reactions and heterogeneous hydrolysis. Because of transboundary transport during the control period, air masses from remote areas contributed significantly to local PM_2.5. Although, secondary organic carbon (OC_sec) exhibited more sensitivity than primary organic carbon (OC_pri) to control measures, and the increased nitrogen oxidation ratio (NOR) implied the regional transport of aged secondary aerosols to the study area. Overall, the results from various approaches revealed that local pollution sources were kept under control, indicating that the implementation of mitigation measures were helpful in improving the air quality of Hangzhou during G20 summit. To reduce ambient levels of PM_2.5 further in Hangzhou, regional control policies may have to be taken so as to reduce the impact of long-range transport of air masses from inland China.

Willingness of rural residents to pay for clean coal and stoves in winter: an empirical study from Zoucheng, Shandong

Addressing climate change and improving air pollution have entered a critical period. Compared with the governance of industrial industries and transportation departments, the regulation of use of scattered coal, an important source of pollution burned by rural households for winter heating, has been relatively neglected. Promoting clean coal and stove products in rural areas is a major measure to mitigate winter pollution, and identifying the key factors influencing rural residents' willingness to pay (WtP) for clean coal and stoves is a prerequisite. This article uses the Tobit model to study the factors influencing rural residents in Zoucheng, Shandong Province, regarding their WtP for clean coal and clean stoves. The empirical analysis results are as follows: (1) The overall level of rural residents' WtP is low, and subsidies remain essential. The total respondent's average WtP for clean stoves was 271.33 yuan (RMB) per unit, and the average WtP for clean coal was 80.28 RMB per ton; the average WtP of the respondents with positive WtP for clean stoves was 321.48 RMB per unit, and the average WtP of the respondents with positive WtP for clean coal was 94.09 RMB per ton. (2) The order and direction of the factors affecting WtP for clean stove were as follows: self-interest values (-)>group norms (+)>past experience (+)>annual household income (+)>subsidy policy promotion (+)>income source (+)>household size (-). (3) The order and direction of the factors affecting the WtP for clean coal were as follows: heating necessity (+)>group norms (+)>past experience (+)>subsidy policy promotion (+)>annual household income (+)>income source (+). Finally, on the basis of the research findings, this paper proposes targeted policy implications to promote clean coal and stoves for the government and enterprises.

The distribution and drivers of PM2.5 in a rapidly urbanizing region: The Belt and Road Initiative in focus

The accelerating urbanization has led to serious air pollution dominated by PM_2.5, posing a critical challenge for the environmental sustainability of the Belt and Road Initiative (BRI). However, a focus on the distribution and drivers of PM_2.5 concentrations in BRI is lacking. To fill in the gap, this study explores the spatio-temporal distribution of PM_2.5 concentrations in 74 nations partnering the BRI and identifies the socioeconomic and natural drivers behind the variation through the joint use of spatial autocorrelation and regression analyses. We find that the PM_2.5 concentrations of BRI show significant spatial autocorrelation and spatial heterogeneity on the national scale. The most heavily polluted regions are observed mainly in China, Southeast Asia, South Asia, West Asia and North Africa, particularly in the Arabian Gulf region. Energy intensity and per capita electricity consumption act as the major drivers of the PM_2.5 concentrations, whereas the expanding forest area contributes to the decrease in PM_2.5 concentrations notably. Our findings highlight the need for speeding up new-type urbanization as part of the green BRI practice, calling for international cooperation and coordinated action aimed at enhancing synergies of air-quality and climate policies that at present are mostly launched and implemented in isolation. From a broader point of view, in struggling towards BRI's cleaner air, more attention should be paid to creating policy synergies between the green BRI, the Paris Agreement, and the United Nations 2030 Agenda for Sustainable Development.

Hourly PM2.5 Estimation over Central and Eastern China Based on Himawari-8 Data

In this study, an improved geographically and temporally weighted regression (IGTWR) model for the estimation of hourly PM2.5 concentration data was applied over central and eastern China in 2017, based on Himawari-8 Advanced Himawari Imager (AHI) data. A generalized distance based on the longitude, latitude, day, hour, and land use type was constructed. AHI aerosol optical depth, surface relative humidity, and boundary layer height (BLH) data were used as independent variables to retrieve the hourly PM2.5 concentrations at 1:00, 2:00, 3:00, 4:00, 5:00, 6:00, 7:00, and 8:00 UTC (Coordinated Universal Time). The model fitting and cross-validation performance were satisfactory. For the model fitting set, the correlation coefficient of determination (R2) between the measured and predicted PM2.5 concentrations was 0.886, and the root-mean-square error (RMSE) of 437,642 samples was only 12.18 µg/m3. The tenfold cross-validation results of the regression model were also acceptable; the correlation coefficient R2 of the measured and predicted results was 0.784, and the RMSE was 20.104 µg/m3, which is only 8 µg/m3 higher than that of the model fitting set. The spatial and temporal characteristics of the hourly PM2.5 concentration in 2017 were revealed. The model also achieved stable performance under haze and dust conditions.

Lung Cancer in Never-Smokers: A Multicenter Case-Control Study in North China

This study aimed at estimating the effects of epidemiological risk factors for lung cancer in never-smokers. A multicenter and matched case-control study was conducted in the cities of Shijiazhuang, Xingtai, Qinhuangdao, Baoding, and Chengde in North China. It comprised 1,086 cases and 2,172 healthy subjects as controls, all of whom had smoked fewer than 100 cigarettes in their lifetimes. Patients were newly diagnosed with lung cancer between January 2015 and December 2017. Each patient was matched to two control participants for sex and age (±5 years). Both univariate analysis and multivariate conditional logistic regression models were used to estimate the odds ratio (OR) and 95% confidence interval (95% CI). Subsequently, data were stratified by participant sex and different air quality conditions for analysis. Type of job, exposure to environmental tobacco smoke in the workplace or at home, above-average exposure to cooking oil fumes, depression, poor sleep quality, occupational exposure, cardiovascular diseases, and family history of cancer were revealed as significant risk factors for lung cancer in never-smokers. However, higher educational level, frequent use of a PM_2.5 mask, cooking using clean fuels, and consumption of dietary supplements and tea reduced the risk of lung cancer. Risk factors varied between males and females. In areas with air pollution, the number of risk factors was greater than elsewhere, and the magnitudes of their effects were different. Hence, focusing on these risk factors is important for the prevention and control of lung cancer in never-smokers.

Escape or stay? Effects of haze pollution on domestic travel: Comparative analysis of different regions in China

Haze pollution has significant impacts on tourist perception and behaviour, including a sharp increase in risk perception and a decline in tourism experience quality. However, given the intervention of multiple factors, whether these impacts necessarily have a negative effect on the overall scale of regional tourism remains unknown. Hence, this paper explored the overall effect of haze pollution on domestic travel. Using 28 major cities in China as examples, we employed a two-way fixed effect panel model to investigate this issue. Combined with the comparisons between the results of different subgroups, including high cities, medium cities, low cities, outbreak cities and non-outbreak cities, this study found that there was no significant effect of haze concentration on domestic travel, but public awareness of haze pollution had a significant positive effect on that. Meanwhile, public awareness exerted a negative moderating effect of haze concentration and domestic travel. The findings are beneficial for understanding the new situation faced by the tourism industry, and several suggestions are provided for policy makers and travel agencies.

Spatiotemporal Trend Analysis of PM2.5 Concentration in China, 1999–2016

China is experiencing severe PM 2 . 5 (fine particles with a diameter of 2.5 μ g or smaller) pollution problem. Little is known, however, about how the increasing concentration trend is spatially distributed, nor whether there are some areas that experience a stable or decreasing concentration trend. Managers and policymakers require such information to make strategic decisions and monitor progress towards management objectives. Here, we present a pixel-based linear trend analysis of annual PM 2 . 5 concentration variation in China during the period 1999–2016, and our results provide guidance about where to prioritize management efforts and affirm the importance of controlling coal energy consumption. We show that 87.9% of the whole China area had an increasing trend. The drastic increasing trends of PM 2 . 5 concentration during the last 18 years in the Beijing–Tianjin–Hebei region, Shandong province, and the Three Northeastern Provinces are discussed. Furthermore, by exploring regional PM 2 . 5 pollution, we find that Tarim Basin endures a high PM 2 . 5 concentration, and this should have some relationship with oil exploration. The relationship between PM 2 . 5 pollution and energy consumption is also discussed. Not only energy structure reconstruction should be repeatedly emphasized, the amount of coal burned should be strictly controlled.

Satellite-Based Estimation of Hourly PM2.5 Concentrations Using a Vertical-Humidity Correction Method from Himawari-AOD in Hebei

Abstract: Particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) is related to various adverse health effects. Ground measurements can yield highly accurate PM2.5 concentrations but have certain limitations in the discussion of spatial-temporal variations in PM2.5. Satellite remote sensing can obtain continuous and long-term coverage data, and many previous studies have demonstrated the relationship between PM2.5 and AOD (aerosol optical depth) from theoretical analysis and observation. In this study, a new aerosol product with a high spatial-temporal resolution retrieved from the AHI (the Advance Himawari Imager) was obtained using a vertical-humidity correction method to estimate hourly PM2.5 concentrations in Hebei. The hygroscopic growth factor (fRH) was fitted at each site (in a total of 137 matched sites). Meanwhile, assuming that there was little change in fRH at a certain scale, the nearest fRH of each pixel was determined to calculate PM2.5 concentrations. Compared to the correlation between AOD and PM2.5, the relationship between the "dry" mass extinction efficiency obtained by vertical-humidity correction and the ground-measured PM2.5 significantly improved, with r coefficient values increasing from 0.19⁻0.47 to 0.61⁻0.76. The satellite-estimated hourly PM2.5 concentrations were consistent with the ground-measured PM2.5, with a high r (0.8 ± 0.07) and a low RMSE (root mean square error, 30.4 ± 5.5 μg/m³) values, and the accuracy in the afternoon (13:00⁻16:00) was higher than that in the morning (09:00⁻12:00). Meanwhile, in a comparison of the daily average PM2.5 concentrations of 11 sites from different cities, the r values were approximately 0.91 ± 0.03, and the RMSEs were between 13.94 and 31.44 μg/m³. Lastly, pollution processes were analyzed, and the analysis indicated that the high spatial-temporal resolution of the PM2.5 data could continuously and intuitively reflect the characteristics of regional pollutants (such as diffusion and accumulation), which is of great significance for the assessment of regional air quality.

Analysis of Spatial-Temporal Characteristics of the PM2.5 Concentrations in Weifang City, China

Air pollution, which accompanies industrial progression and urbanization, has become an urgent issue to address in contemporary society. As a result, our understanding and continued study of the spatial-temporal characteristics of a major pollutant, defined as 2.5-micron or less particulate matter (PM2.5), as well as the development of related approaches to improve the environment, has become vital. This paper studies the characteristics of yearly, quarterly, monthly, daily, and hourly PM2.5 concentrations, and discusses the influencing factors based on the hourly data of nationally controlled and provincially controlled monitoring stations, from 2012 to 2016, in Weifang City. The main conclusion of this study is that the annual PM2.5 concentrations reached a peak in 2013. With efficient aid from the government, this value has decreased annually and has high spatial characteristics in the northwest and low spatial characteristics in the southeast. Second, the seasonal and monthly PM2.5 concentrations form a U-shaped trend, meaning that the concentration is high in the summer and low in the winter. These trends are highly relevant to the factors of plantation, humidity, temperature, and precipitation. Third, within a week, higher PM2.5 concentrations appear on Mondays and Saturdays, whereas the lowest concentration occurs on Wednesdays. It can be inferred that PM2.5 concentrations tend to be highly dependent on human activities and living habits. Lastly, there are hourly discrepancies within the peaks and troughs depending on the month, and the overall daytime PM2.5 concentrations and reductive rates are higher in the daytime than in the nighttime.

Fine particulate matter associated mortality burden of lung cancer in Hebei Province, China

BACKGROUND

The association between fine particulate matter (PM_2.5 ) and lung cancer (LC) mortality in China is limited. The Beijing-Tianjin-Hebei region is infamous for serious air pollution. Seven of the top 10 cities with the worst air quality are located in Hebei Province. Thus, we explored the effect of 10 years of PM_2.5 on the LC mortality rate in Hebei Province.

METHODS

We quantified associations between LC mortality and PM_2.5 and estimated the LC mortality burden attributed to PM_2.5 with predicted county level LC deaths in 2014.

RESULTS

The 10-year PM_2.5 LC mortality associations were non-linear, with thresholds of 63 μg/m³ overall, 69 μg/m³ for men, 68 μg/m³ for women, 66 μg/m³ for those aged 30-64 years, and 62 μg/m³ for those aged ≥ 65 years. The relative risks for these groups were 1.09 (95% confidence interval [CI] 1.08-1.10), 1.06 (95% CI 1.03-1.10), 1.20 (95% CI 1.10-1.26), 1.07 (95% CI 1.05-1.11), and 1.10 (95% CI: 1.07-1.13), respectively. There were 2525 (95% CI 2265-2780) LC deaths attributed to 10-year PM_2.5 in 2014, at fractions of 8.3% (95% CI 7.4-9.1%) overall, 5.7% (95% CI 2.8-9.4%) for men, 16.7% (95% CI: 8.3-21.6%) for women, 6.5% (95% CI 4.7-10.3%) for those aged 30-64 years, and 9.1% (95% CI 6.4-11.5%) for those aged ≥ 65 years.

CONCLUSION

Our results suggest that a reduction in the PM_2.5 exposure levels below thresholds would prevent a substantial number of LC deaths in Hebei Province.