Spatial distribution, seasonal variation and regionalization of PM2.5 concentrations in China

The role of large-scale atmospheric circulations on long-term variations of PM10 concentrations over Turkey

PM10 is widely identified as an important atmospheric pollutant posing a serious threat to human health and environment as well as it influences the climate system. To unearth the mechanism involved in its sources and circulation behavior in environment, this study focuses on the role of large-scale atmospheric circulation on the long-term variability of PM10 over Turkey by applying rotated empirical orthogonal functions (REOF) analysis. As a result of the implementation of REOF to the daily PM10 data for 80 air quality stations throughout the period 2010-2020, first REOF mode (REOF1 44.9% in winter, 43.2% in spring, 39.5% in summer and 31.6% in fall) for all the four seasons indicated the role of local emission sources on the variations of PM10, which show high PM10 values in different geographical regions. The results of the second mode (REOF2, 17.9% in winter, 14.0% in spring, 14.0% in summer and 16.3% in fall) indicate the role of large-scale atmospheric circulations on the values of PM10. From the REOF2 analysis and extracted synoptic composite maps, the strength of southerly winds and the presence of southwesterly winds at low levels are very important in transporting of dust pollutants from the Arabian Peninsula and Northern Africa, respectively, to the eastern (EAR) and southeastern (SEAR) regions of Turkey during winter. In spring, sand particles in the interior terrestrial part of the country are carried to the northern regions by the effect of large-scale southerly winds, which cause above-normal PM10 concentrations in the Black Sea region of Turkey. In summer, dust particles together with warm dry air intrusion to the eastern region of Turkey by strong easterly winds are sourced by Caspian Sea and result in high PM10 values. Our findings emphasize that the long-term variations in air quality over Turkey are affected secondary by the variations in the large-scale atmospheric circulations with primary contributions from the changes in local emission sources.

Assessment of variability in PM2.5 and its impact on human health in a West African country

PM2.5 has become a global challenge threatening human health, climate, and the environment. PM2.5 is ranked as the most common cause of premature mortality and morbidity. Therefore, the current study endeavors to probe the spatiodynamic characteristics of PM2.5 in the Republic of Niger and its impacts on human health from 1998 to 2019. Based on remotely sensed satellite datasets, the study found that the concentration of PM2.5 continued to rise in Niger from 68.85 μg/m3 in 1998 to 70.47 μg/m3 in 2019. During the study period, the annual average PM2.5 concentration is far above the WHO guidelines and the interim target-1 (35 μg/m3). The overall annual growth rate of PM2.5 concentration in Niger is 0.02 μg/m3/year. The health risk (HR) due to PM2.5 exposure is also escalated in Niger, particularly, in Southern Niger. The extent of the extremely high-risk areas corresponding to 1 × 104-9.4 × 105 μg.persons/m3 is increased from 0.9% (2000) to 2.8% (2019). Niamey, southern Dakoro, Mayahi, Tessaoua, Mirriah, Magaria, Matameye, Aguié, Madarounfa, Groumdji, Madaoua, Bouza, Keita, eastern Tahoua, eastern Illéla, Bkomnni, southern Dogon-Doutchi, Gaya, eastern Boboye, central Kollo, and western Tillabéry are experienced high HR due to long-term exposure to PM2.5. These findings indicate that PM2.5 causes a serious health risk across Niger. There is an immediate need to carry out its regional control. Therefore, policymakers and the Nigerien government should make conscious efforts to identify the priority target areas with radically innovative appropriate mitigation interventions.

A new approach of air pollution regionalization based on geographically weighted variations for multi-pollutants in China

Air pollution regionalization is a key and necessary action to identify pollution regions for implementing control measures. Here we present a new approach called Geographically Weighted Rotation Empirical Orthogonal Function (GWREOF) for air pollution regionalization in China. Compared with previous methods, such as EOF, REOF, and K-mean, GWREOF better accounts for the variability of air pollution conditions driven by emission patterns and meteorology with centralized spatial locations. We apply GWREOF to multiple air pollutants (such as PM_2.5, O₃, and other monitored air pollutants) and air quality metrics using their measured spatial and temporal variations in 337 Chinese cities over 2015-2020. We find that the regionalization results for different air pollutants are highly similar, primarily determined by topography and meteorological conditions in China. Therefore, we propose an integrated regionalization result, which identifies 18 air pollution control regions in China and can be applied to multiple pollutants and different years. We further analyze PM_2.5, O₃, and O_X (O₃ + NO₂) pollution levels and their correlations in these regions. PM_2.5 and O₃ correlations are generally strongly positive in southern China while negative in northern China. However, PM_2.5 and O_X correlations are broadly positive in China, reflecting the crucial role of atmospheric oxidizing capacity. Regional-specific and coordinated control measures are in need as China's air pollution strategy transits from PM_2.5-focused to PM_2.5-O₃ synergic control.

Analysis of Worldwide Greenhouse and Carbon Monoxide Gas Emissions: Which Countries Exhibit a Special Pattern? A Closer Look via Twitter

There is significant global concern about the harmful effects of greenhouse gas and carbon monoxide emissions (deforestation, air pollution, global warming, etc.). The 2015 Paris Agreement on climate change aspires to reduce global warming by achieving a climate-neutral world. Research has been carried out to calculate and diminish the aforementioned emissions in waste, power industry, transport, building, in addition to other areas. The aim of this paper is to analyse the carbon and greenhouse gas emissions across countries around the globe in order to find patterns and correlate them to socio-economic indicators [gross national income (GNI), industrial production (IPI) and human development indexes (HDI)] as well as Twitter interactions regarding climate change. For this purpose, time series and socio-economic data have been downloaded from different repositories including EDGAR (Emissions Database for Global Atmospheric Research), World Bank and UNDP (United Nations Development Programme). Although classical clustering algorithms have already been used in the examination of some environmental issues, we use a non-parametric time series clustering method, which has been suggested in certain scientific literature as a more flexible approach, since any ad hoc parametric assumptions are required. The chosen socio-economic indicators have also demonstrated their relevance in pieces of research related to various fields. With respect to Twitter, which is one of the most popular social networks nowadays, significant analysis has also been performed on the basis of capturing citizens' perceptions on a multitude of matters. We found that several countries such as Brazil, India, China, Nigeria, Russia, United States, Spain, Andorra, Greece, and Qatar show differences in carbon and greenhouse gas emissions patterns. Besides, there does not seem to be a correlation between GNI, IPI and HDI as well as the above mentioned emissions ( correlation < 0.16 ) . Regarding Twitter interactions, a dissimilarity in the distribution of hashtags was detected between the aforementioned countries and the rest of the world. This research can help to identify countries in which more governmental measures are needed to reduce the type of emissions analysed in certain industrial sectors. In addition, it points out the topics related to climate change that seem to generate the most debate on Twitter for countries with an unusual pattern.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41742-023-00510-4.

Spatiotemporal distribution characteristics of PM2.5 concentration in China from 2000 to 2018 and its impact on population

PM2.5 is an important indicator reflecting changes in air quality. In recent years, affected by climate change and human activities, the problem of environmental pollution has become more and more prominent. In this study, the PM2.5 data from 2000 to 2018 obtained by satellite remote sensing inversion algorithm were selected to analyze the temporal and spatial distribution of PM2.5 in China. The results show that the areas with higher PM2.5 concentrations were mainly in the North China, the Sichuan Basin, and the Tarim Basin. The areas with a significant increase in PM2.5 were mainly in the Northeast China, while the areas with a significant decrease were mainly in the Sichuan Basin and southeastern Gansu. The change of PM2.5 in southern China was not significantly correlated with the change of population and economy, while PM2.5 in Northeast China increases with the increase of population and economy. In 2000, 2005, 2010, and 2015, the proportion of the population polluted by PM2.5 was 8.65%, 7.2%, 22.99%, and 9.75%, respectively. The year with the highest percentage (37.63%) of population when air quality reached EXCELLENT was 2015. When the PM2.5 spatial cluster number was six, it can better reflect the PM2.5 spatial distribution state. The places with large changes in PM2.5 spatial clustering were mainly in the Northeast China, Sichuan Basin, and Tarim Basin, which were also areas with large changes in PM2.5. This study provides an important reference for atmospheric environmental monitoring and protection.

Personal exposure to PM2.5 of indoor and outdoor origin in two neighboring Chinese communities with contrasting household fuel use patterns

The Chinese government is replacing high-polluting, household coal heating stoves with electricity- and natural gas-powered heaters to improve ambient air quality. The evaluation of the intervention impact on outdoor PM_2.5 and personal exposure in community level are in their initial stages. We compared outdoor air pollution and personal exposure in two neighboring communities (~2 km) in northern China with contrasting household fuel use patterns: one where residents primarily used coal for cooking and heating ("coal village") and one where natural gas was the dominant fuel ("gas village"). We collected 24-h outdoor gravimetric PM_2.5 samples in each village and concurrently measured 48-h integrated exposures among 71 participants from 41 and 30 households in the coal and gas villages, respectively. PM_2.5 samples were analyzed for mass and chemical composition. Daily outdoor PM_2.5 concentrations in the coal village (mean ± standard deviation: 109 ± 41 μg/m³) were, on average, 1.3 ± 0.2 times higher than in the gas village (88 ± 38 μg/m³). However, personal PM_2.5 exposures were lower in the coal village (116 ± 121 μg/m³ versus 156 ± 106 μg/m³). PM_2.5 species that can serve as tracers for residential coal combustion (e.g., S, Se, Zn, Pb, etc.) and dust (Al, Ca, Mg, Fe, Si and Ti) were higher in the coal village, and the proportion of personal PM_2.5 of outdoor origin in the coal village was nearly 2 times higher than the gas village. Our results suggest that ambient PM_2.5 and its chemical composition can vary at relatively small spatial scales and may reflect community-level differences in the household energy use. However, personal PM_2.5 exposures may not mirror between-village differences in outdoor air pollution if only PM_2.5 mass is evaluated. Individual chemical composition of PM_2.5 exposure can provide important insight in future studies on the effectiveness of source-targeted air quality interventions.

Environmental implications of reduced electricity consumption in Wuhan during COVID-19 outbreak: A brief study

Due to the COVID-19 outbreak, Wuhan was locked down from 23 January 2020 to 8 April 2020, a total of 76 days. It is well known that the electricity consumption is a direct reflection of human activity. During the lockdown of Wuhan, most of human activities were forbidden. The reduction in human activity would inevitably lead to a reduction in electricity consumption. At the same time, anthropogenic emissions of air pollutants would also be reduced with the reduction of human activity. In this study, the correlation between electricity consumption and air pollutants during lockdown was discussed in detail. The result showed that the drop in pollutants concentrations in January should be attributed to the washout effect of rainfall rather than the lockdown. The decrease of electricity consumption in the secondary industry might play a significant role on the decrease of PM2.5 and NO2 concentrations in Wuhan in February 2020. The decrease in NO2 concentration in March should be attributed to the reduction of pollutants emissions from the tertiary industry, which means that more attention should be paid to the control of NO2 emission in the tertiary industry. Due to reduced emissions from local sources, the role of long-range transport sources might be more significant during the lockdown of Wuhan. By PSCF analysis, southeast of Wuhan could be the major potential emission sources of PM2.5 , especially in the northern part of Jiangxi province. It was suggested that stricter regulation of pollutants emissions should be implemented in this area.

Affinity zone identification approach for joint control of PM2.5 pollution over China

In recent years, the Chinese government has made great efforts to jointly control and prevent air pollution, especially fine particulate matter (PM_2.5). However, these efforts are challenged by technical constraints due to the significant temporal and spatial heterogeneity of PM_2.5 across China. In this study, the Affinity Zone Identification Approach (AZIA), which combines rotated principal component analysis (RPCA) with revised clustering analysis, was developed and employed to regionalize PM_2.5 pollution in China based on data from 1496 air quality monitoring sites recorded from 2013 to 2017. Two clustering methods, cluster analysis with statistical test (CAST) and K-center-point (K-medoids) clustering, were compared and revised to eliminate unspecified sites. Site zonation was finally extended to the municipality scale for the convenience of the controlling measures. The results revealed that 17 affinity zones with 5 different labels from clean to heavily polluted areas could be identified in China. The heavily polluted areas were mainly located in central and eastern China as well as Xinjiang Province, with regional average annual PM_2.5 concentrations higher than 66 μg/m³. The new approach provided more comprehensive and detailed affinity zones than obtained in a previous study (Wang et al., 2015b). The North China Plain and Northeastern China were both further divided into northern and southern parts based on different pollution levels. In addition, five affinity zones were first recognized in western China. The findings provide not only a theoretical basis to further display the temporal and spatial variations in PM_2.5 but also an effective solution for the cooperative control of air pollution in China.

The changing PM2.5 dynamics of global megacities based on long-term remotely sensed observations

Satellite observations show that the rapid urbanization and emergence of megacities with 10 million or more residents have raised PM2.5 concentrations across the globe during the past few decades. This study examines PM2.5 dynamics for the 33 cities included on the UN list of megacities published in 2018. These megacities were classified into densely (>1500 residents per km²), moderately (300-1500 residents per km²) and sparsely (<300 residents per km²) populated areas to examine the effect of human population density on PM2.5 concentrations in these areas during the period 1998-2016. We found that: (1) the higher population density areas experienced higher PM2.5 concentrations; and (2) the megacities with high PM2.5 concentrations in these areas had higher concentrations than those in the moderately and sparsely populated areas of other megacities as well. The numbers of residents experiencing poor air quality is substantial: approximately 452 and 163 million experienced average annual PM2.5 levels exceeding 10 and 35 μg/m³, respectively in 2016. We also examined PM2.5 trends during the past 18 years and predict that high PM2.5 levels will likely continue in many of these megacities in the future without substantial changes in their economies and/or pollution abatement practices. There will be more megacities in the highest PM2.5 pollution class and the number of megacities in the lowest PM2.5 pollution class will likely not change. Finally, we analyzed how the PM2.5 pollution burden varies geographically and ranked the 33 megacities in terms of PM2.5 pollution in 2016. The most polluted regions are China, India, and South Asia and the least polluted regions are Europe and Japan. None of the 33 megacities currently fall in the WHO's PM2.5 attainment class (<10 μg/m³) while 9 megacities fall into the PM2.5 non-attainment class (>35 μg/m³). In 2016, the least polluted megacity was New York and most polluted megacity was Delhi whose average annual PM2.5 concentration of 110 μg/m³ is nearly three times the WHO's non-attainment threshold.

Particulate matter transported from urban greening plants during precipitation events in Beijing, China

Particulate matter (PM) deposited on canopy surfaces could be washed off and carried in throughfall to the ground. This would help plants recapture airborne PM on their canopy surfaces and then develop a PM purification capacity. Sixteen commonly greening plant species in north China (including 13 arbor species and 3 shrub species) were selected to investigate the washing process of plant-deposited PM during precipitation events. We measured the PM wash-off mass in throughfall under canopies of 16 plant species and in atmospheric precipitation during 14 precipitation events through field positioning experiments in 2015, compared the seasonal changes and species differences in PM wash-off mass, and discussed the predominant factors resulting in the variation. The results showed that plant-deposited PM was largely washed off by precipitation. The average wash-off mass of total suspended particulate (TSP) in throughfall was 1.3 times higher than that in precipitation, at 18.3 ± 0.7 kg hm^-2 and 7.9 ± 0.9 kg hm^-2, respectively. There were significant seasonal differences in TSP wash-off mass. The value was higher in summer at 22.3 ± 1.0 kg hm^-2, followed by that of winter (10.8 ± 0.6 kg hm^-2) and spring (8.9 ± 1.0 kg hm^-2). TSP wash-off mass in throughfall greatly varied among plant species (F = 9.542, n = 627, p < 0.001). Of the 16 selected species, Platanus acerifolia (38.0 ± 5.8 kg hm^-2) showed the largest difference from that of Liriodendron chinese (8.9 ± 0.6 kg hm^-2) (n = 80, p < 0.001). PM wash-off mass of different particle sizes in throughfall increased with the increase of event-based precipitation. This study enhanced the quantitative understanding of plant-deposited PM washed-off by natural precipitation among plant species and seasons. The results could provide significant guidelines for the selection and allocation of plant species to improve the PM retention capacity of urban greening plants.

National air pollution distribution in China and related geographic, gaseous pollutant, and socio-economic factors

Regional specification of PM_2.5 pollution characteristics is crucial for pollution control and policymaking. Spatiotemporal variations of six criteria air pollutants and influencing factors in China were studied using hourly concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ from 2015 to 2016. China was categorized into eight regions: north-east, northern coastland, eastern coastland, southern coastland, Yellow River middle reaches, Yangtze River middle reaches, south-west, and north-west. The 29 exemplary cities in China were also researched. It was found that the PM_2.5 concentration in the northern coastland (Beijing-Tianjin-Hebei-Shandong) was the highest (72.28 μg.m^-3) among the eight regions, particularly in the city of Baoding, Hebei, which had an annual average PM_2.5 concentration of 98.53 μg.m^-3. Average PM_2.5 concentrations in 2015 and 2016 of China were 50.16 μg.m^-3 and 46.61 μg.m^-3, respectively. Compared with 2015, the PM_2.5 concentration decreased by 8.41% in 2016, the decline of PM_2.5 in summer was the largest, followed by autumn, spring and winter. The average mean PM_2.5 concentrations of the 29 exemplary cities in 2015 and 2016 were 54.66 μg.m^-3 and 48.37 μg.m^-3, respectively, exceeding the limit for grade 2 of the national standards (35 μg.m^-3). National air pollution distribution has exploded geographically with influence of regional economic factors. Gaseous pollutant as well as geographical and socio-economic conditions influenced PM_2.5 emissions. Effects of these factors on PM_2.5 emissions varied across regions and decreased continuously from the northern region to the south-west and eastern coastland regions. This paper clearly identifies the regional characteristics and distribution of PM_2.5, focusing on the effects of gaseous pollutant, geography and socio-economic development. Secondary transformation and vehicle exhaust across regions should be further studied.

Difference of Airborne Particulate Matter Concentration in Urban Space with Different Green Coverage Rates in Baoji, China

With the acceleration of urbanization and industrialization, the problem of airborne particulate pollution has become more and more serious. Green areas in urban spaces with different green coverage rates in Baoji City were selected to quantitatively compare the effects and differences of month, time, temperature, humidity, wind velocity, vegetation structure, and area of site on PM2.5 and PM10 concentration. The results showed that increasing the urban green coverage rate will help to improve the green area's reduction of airborne particulate matter concentration and the selected factors affecting the green area's reduction ability were discrepant in urban spaces with different green coverage rates. With the decrease of the green coverage rate, the purification effect of green area itself on air particles was weakened, and other factors, such as meteorological conditions and human activities, became the dominant influencing factors. Vegetation structure only had significant effects on the concentration of PM2.5 and PM10 in green areas of urban space with a green coverage rate greater than 75%. The concentration of PM2.5 and PM10 were lowest in the partly closed green area of one-layered coniferous trees and the closed green area of one-layered mixed trees. The research shows that green areas in urban spaces with different green coverage rates have different reduction effects on the concentration of airborne particles, which provides a theoretical basis and reference for the optimization of green area structures and to improve air quality effectively in the future.

Long-term spatiotemporal variations of atmospheric sulfur, nitrogen and particle pollutants in Chongqing, southwest China: implication of industrial transfer

Industrial transfer has swept through in China. However, there is still a knowledge gap about its environmental effects. In this study, industrial transfer status was assessed and evaluated by industrial ratios (%; the gross product contributions of the secondary industry to the whole industry) and the impact of such transfer on atmospheric environment (SO₂, NO₂, PM₁₀ (particles with aerodynamic diameter less than 10 μm), precipitations of SO₄^2-, NO₃^-, and NH₄⁺) in the 38 districts and counties in Chongqing was analyzed and discussed for the period of 2006-2015. Results showed that industries were transferred obviously from the main urban region (MUR) into the 1-h economic region (OHER). Atmospheric sulfur and PM₁₀ were efficiently put in control, but atmospheric nitrogen (NO₂; precipitations of NO₃^- and NH₄⁺) was increasing and posted a potential threat to air quality especially during 2011-2015. Correlations showed that industrial ratios had significantly positive relationships with concentrations of ambient SO₂ and PM₁₀ in the MUR and ambient NO₂ in the OHER (p < 0.05) while a remarkably negative one with concentrations of ambient SO₂ in the OHER (p < 0.05) during 2006-2015, implying that industrial transfer could be effective in transferring sulfur pollution but not as efficient in transferring atmospheric nitrogen and PM₁₀ pollutions as SO₂ between in the MUR and OHER. More measures should be taken to reduce nitrogen and PM₁₀ emission and a regional monitoring network of ambient NH₃ is in urgent need.

Indoor Exposure to Ambient Particles and Its Estimation Using Fixed Site Monitors

Ambient PM_2.5 concentrations measured at fixed site monitors (FSM) are often biased with respect to exposure concentrations because of spatial variability and infiltration. Based on comparison of ambient concentrations from 14 FSMs and of exposure concentrations measured indoors and outdoors at two schools in Hong Kong for winter and summer seasons, the magnitude and sources of exposure error based on using FSMs as a surrogate for exposure are quantified. An approach for bias correcting surrogate exposure estimates from FSMs is demonstrated. The approach is based on a proximity factor (PF) that accounts for differences in spatial locations, proximity to emissions and deviation from dominant wind direction, and an infiltration factor (IF) that varies by season. The combination of the PF and IF reduce bias in mean school exposure estimates from ±90% to ±20%. Bias in exposure estimates from using FSMs as surrogates tend to be smaller for which the exposure site and FSM are aligned with wind direction, have similar sampling height, and are in close proximity. The methodology demonstrated to assess concordance between FSMs and exposure measurement sites can be applied more broadly to help reduce exposure error, which may help to interpret seasonal variations in health estimates.

Fluctuation in time-resolved PM2.5 from rural households with solid fuel-associated internal emission sources

Indoor air contributes significantly to overall exposure, particularly for rural Chinese who often use solid fuels for cooking and/or heating. Unfortunately, overlooked rural indoor air leads to a critical knowledge gap. Simultaneous measurements in the kitchen, living room, and immediately outside of houses using six-channel particle counters were carried out in 18 biomass-burning rural and 3 non-biomass-burning urban households (as a comparison) in winter to characterize dynamic change patterns indoor air pollution and indoor-outdoor relationship. The rural households mainly used wood or crop residues for cooking and heating, while the urban households used pipelined natural gas for cooking and air conditioners for heating. In rural households with significant solid-fuel burning internal sources, the highest concentration was found in the kitchen (101 ± 56 μg/m³), with comparable levels in the living room (99 ± 46 μg/m³) and low levels in outdoor air (91 ± 39 μg/m³). A generally opposite direction of indoor-outdoor exchange was found between the rural and urban households. PM in kitchen air is smaller than that in living rooms and outdoors because solid fuel burning (mainly in rural households) and cooking oil heating (in rural and urban households). Indoor and outdoor PM concentration changed synchronously, with a slight delay in indoor air in urban households but a slight delay in outdoor air in rural households. Cooking, heating, and smoking elevated indoor PM significantly, but different from the cooking activity that produced peaks lasting for about 30 min, emissions from heating created a series of peaks due to frequent disturbance and fuel-feeding and had more significant impacts on the daily average concentration. Distinct indoor-outdoor relationships and dynamic change patterns between the two household categories w/o strong internal biomass burning sources imply that totally different model schemes are needed to quantitatively address indoor air pollution and inhalation exposure.

The Reducing Effect of Green Spaces with Different Vegetation Structure on Atmospheric Particulate Matter Concentration in BaoJi City, China

With the acceleration of urbanisation and industrialisation, atmospheric particulate pollution has become one of the most serious environmental problems in China. In this study, green spaces in Baoji city were classified into different patterns on the basis of vegetation structural parameters, i.e., horizontal structure, vertical structure and vegetation type. Eleven types of green space with different structures were selected for investigating the relationships between atmospheric particulate matter (PM) concentration and green spaces with different vegetation structure, based on the “matrix effect” of environmental factors, i.e., location, time, wind velocity, temperature, humidity and area to the concentration of PM2.5 and PM10 in the green spaces. The results showed that: (1) Location, time, wind velocity, temperature and humidity had highly significant effects on the concentration of PM2.5 and PM10. In sunny and breeze weather conditions, PM2.5 and PM10 concentration increased with the wind velocity and humidity, and decreased with the temperature. The range of PM10 concentration was greater than the range of PM2.5 concentration. (2) Less than 2 hectares of the green space had no significant influence on the concentration of PM2.5 and PM10. (3) The concentration of PM2.5 and PM10 showed no significant difference between all the green spaces and the control group. There was no significant difference in the reduction of PM2.5 concentration between different structural green spaces, but there was a significant difference in the reduction of PM10 concentration. The above results will provide a theoretical basis and practical methods for the optimisation of urban green space structures for improving urban air quality effectively in the future.

Regionalization based on spatial and seasonal variation in ground-level ozone concentrations across China

Owing to the vast territory of China and strong regional characteristic of ozone pollution, it's desirable for policy makers to have a targeted and prioritized regulation and ozone pollution control strategy in China based on scientific evidences. It's important to assess its current pollution status as well as spatial and temporal variation patterns across China. Recent advances of national monitoring networks provide an opportunity to insight the actions of ozone pollution. Here, we present rotated empirical orthogonal function (REOF) analysis that was used on studying the spatiotemporal characteristics of daily ozone concentrations. Based on results of REOF analysis in pollution seasons for 3years' observations, twelve regions with clear patterns were identified in China. The patterns of temporal variation of ozone in each region were separated well and different from each other, reflecting local meteorological, photochemical or pollution features. A rising trend in annual averaged Eight-hour Average Ozone Concentrations (O₃-8hr) from 2014 to 2016 was observed for all regions, except for the Tibetan Plateau. The mean values of annual and 90 percentile concentrations for all 338 cities were 82.6±14.6 and 133.9±25.8μg/m³, respectively, in 2015. The regionalization results of ozone were found to be influenced greatly by terrain features, indicating significant terrain and landform effects on ozone spatial correlations. Among 12 regions, North China Plain, Huanghuai Plain, Central Yangtze River Plain, Pearl River Delta and Sichuan Basin were realized as priority regions for mitigation strategies, due to their higher ozone concentrations and dense population.

Spatio-temporal variations in PM leaf deposition: A meta-analysis

Particulate matter (PM) pollution in urban cities is of great concern for public health due to its global and adverse effect of human health while ecosystems function and vegetation control is an effective and eco-friendly way to alleviate PM pollution. We reviewed 150 studies conducted in 15 countries that were published between 1960 and 2016 and used a meta-analysis to examine the time trends and regional differences in leaf deposited PM of urban greening plants. The results suggested that the weekly PM leaf deposition varied markedly with both plant species and space-time and the average value was 1.71 ± 0.05 g m^-2·wk^-1, and the variations occurred because of vegetation factors, characteristics of the PM source and meteorological factors. Moreover, fine particulate matter accounts for the minimum proportion of the total PM mass but its number ratio is maximum, more than 90% of the total number of particles. This meta-analysis illustrated the spatio-temporal trends and variations in PM leaf deposition and the influencing factors, which provides a scientific basis for the mechanism of PM deposition on leaf surface as well as plant selection and configuration in urban greening.

An evaluation of the ecological and environmental security on China's terrestrial ecosystems

With rapid economic growth, industrialization, and urbanization, various ecological and environmental problems occur, which threaten and undermine the sustainable development and domestic survival of China. On the national scale, our progress remains in a state of qualitative or semi-quantitative evaluation, lacking a quantitative evaluation and a spatial visualization of ecological and environmental security. This study collected 14 indictors of water, land, air, and biodiversity securities to compile a spatial evaluation of ecological and environmental security in terrestrial ecosystems of China. With area-weighted normalization and scaling transformations, the veto aggregation (focusing on the limit indicator) and balanced aggregation (measuring balanced performance among different indicators) methods were used to aggregate security evaluation indicators. Results showed that water, land, air, and biodiversity securities presented different spatial distributions. A relatively serious ecological and environmental security crisis was found in China, but presented an obviously spatial variation of security evaluation scores. Hotspot areas at the danger level, which are scattered throughout the entirety of the country, were identified. The spatial diversities and causes of ecological and environmental problems in different regions were analyzed. Spatial integration of regional development and proposals for improving the ecological and environmental security were put forward.

Village energy survey reveals missing rural raw coal in northern China: Significance in science and policy

Burning coal for winter heating has been considered a major contributor to northern China's winter haze, with the district heating boilers holding the balance. However a decade of intensive efforts on district heating boilers brought few improvements to northern China's winter air quality, arousing a speculation that the household heating stoves mainly in rural area rather than the district heating boilers mainly in urban area dominate coal emissions in winter. This implies an extreme underestimation of rural household coal consumption by the China Energy Statistical Yearbooks (CESYs), although direct evidence supporting this speculation is lacking. A village energy survey campaign was launched to gather the firsthand information on household coal consumption in the rural areas of two cities, Baoding (in Hebei province) and Beijing (the capital of China). The survey data show that the rural raw coal consumption in Baoding (5.04 × 10³ kt) was approximately 6.5 times the value listed in the official CESY 2013 and exceeded the rural total of whole Hebei Province (4668 kt), revealing a huge amount of raw coal missing from the current statistical system. More importantly, rural emissions of particulate matter (PM) and SO₂ from raw coal, which had never been included in widely distributing environmental statistical reports, were found higher than those from industrial and urban household sectors in the two cities in 2013, which highlights the importance of rural coal burning in creating northern China's heavy haze and helps to explain why a number of modeling predictions on ambient pollutant concentrations based on normal emission inventories were more bias-prone in winter season than in other seasons. We therefore recommend placing greater emphasis on the "missing" rural raw coal to help China in its long-term ambition to achieve clean air in the context of rapid economic development.

Preterm birth associated with maternal fine particulate matter exposure: A global, regional and national assessment

Reduction of preterm births (<37 completed weeks of gestation) would substantially reduce neonatal and infant mortality, and deleterious health effects in survivors. Maternal fine particulate matter (PM_2.5) exposure has been identified as a possible risk factor contributing to preterm birth. The aim of this study was to produce the first estimates of ambient PM_2.5-associated preterm births for 183 individual countries and globally. To do this, national, population-weighted, annual average ambient PM_2.5 concentration, preterm birth rate and number of livebirths were combined to calculate the number of PM_2.5-associated preterm births in 2010 for 183 countries. Uncertainty was quantified using Monte-Carlo simulations, and analyses were undertaken to investigate the sensitivity of PM_2.5-associated preterm birth estimates to assumptions about the shape of the concentration-response function at low and high PM_2.5 exposures, inclusion of provider-initiated preterm births, and exposure to indoor air pollution. Globally, in 2010, the number of PM_2.5-associated preterm births was estimated as 2.7 million (1.8-3.5 million, 18% (12-24%) of total preterm births globally) with a low concentration cut-off (LCC) set at 10μgm^-3, and 3.4 million (2.4-4.2 million, 23% (16-28%)) with a LCC of 4.3μgm^-3. South and East Asia, North Africa/Middle East and West sub-Saharan Africa had the largest contribution to the global total, and the largest percentage of preterm births associated with PM_2.5. Sensitivity analyses showed that PM_2.5-associated preterm birth estimates were 24% lower when provider-initiated preterm births were excluded, 38-51% lower when risk was confined to the PM_2.5 exposure range in the studies used to derive the effect estimate, and 56% lower when mothers who live in households that cook with solid fuels (and whose personal PM_2.5 exposure is likely dominated by indoor air pollution) were excluded. The concentration-response function applied here derives from a meta-analysis of studies, most of which were conducted in the US and Europe, and its application to the areas of the world where we estimate the greatest effects on preterm births remains uncertain. Nevertheless, the substantial percentage of preterm births estimated to be associated with anthropogenic PM_2.5 (18% (13%-24%) of total preterm births globally) indicates that reduction of maternal PM_2.5 exposure through emission reduction strategies should be considered alongside mitigation of other risk factors associated with preterm births.

Long-term trend and spatial pattern of PM2.5 induced premature mortality in China

With rapid economic growth, China has witnessed increasingly frequent and severe haze and smog episodes over the past decade, posing serious health impacts to the Chinese population, especially those in densely populated city clusters. Quantification of the spatial and temporal variation of health impacts attributable to ambient fine particulate matter (PM_2.5) has important implications for China's policies on air pollution control. In this study, we evaluated the spatial distribution of premature deaths in China between 2000 and 2010 attributable to ambient PM_2.5 in accord with the Global Burden of Disease based on a high resolution population density map of China, satellite retrieved PM_2.5 concentrations, and provincial health data. Our results suggest that China's anthropogenic ambient PM_2.5 led to 1,255,400 premature deaths in 2010, 42% higher than the level in 2000. Besides increased PM_2.5 concentration, rapid urbanization has attracted large population migration into the more developed eastern coastal urban areas, intensifying the overall health impact. In addition, our analysis implies that health burdens were exacerbated in some developing inner provinces with high population density (e.g. Henan, Anhui, Sichuan) because of the relocation of more polluting and resource-intensive industries into these regions. In order to avoid such national level environmental inequities, China's regulations on PM_2.5 should not be loosened in inner provinces. Furthermore policies should create incentive mechanisms that can promote transfer of advanced production and emissions control technologies from the coastal regions to the interior regions.

Seasonal variation in outdoor, indoor, and personal air pollution exposures of women using wood stoves in the Tibetan Plateau: Baseline assessment for an energy intervention study

Cooking and heating with coal and biomass is the main source of household air pollution in China and a leading contributor to disease burden. As part of a baseline assessment for a household energy intervention program, we enrolled 205 adult women cooking with biomass fuels in Sichuan, China and measured their 48-h personal exposure to fine particulate matter (PM2.5) and carbon monoxide (CO) in winter and summer. We also measured the indoor 48-h PM2.5 concentrations in their homes and conducted outdoor PM2.5 measurements during 101 (74) days in summer (winter). Indoor concentrations of CO and nitrogen oxides (NO, NO2) were measured over 48-h in a subset of ~80 homes. Women's geometric mean 48-h exposure to PM2.5 was 80μg/m(3) (95% CI: 74, 87) in summer and twice as high in winter (169μg/m(3) (95% CI: 150, 190), with similar seasonal trends for indoor PM2.5 concentrations (winter: 252μg/m(3); 95% CI: 215, 295; summer: 101μg/m(3); 95% CI: 91, 112). We found a moderately strong relationship between indoor PM2.5 and CO (r=0.60, 95% CI: 0.46, 0.72), and a weak correlation between personal PM2.5 and CO (r=0.41, 95% CI: -0.02, 0.71). NO2/NO ratios were higher in summer (range: 0.01 to 0.68) than in winter (range: 0 to 0.11), suggesting outdoor formation of NO2 via reaction of NO with ozone is a more important source of NO2 than biomass combustion indoors. The predictors of women's personal exposure to PM2.5 differed by season. In winter, our results show that primary heating with a low-polluting fuel (i.e., electric stove or wood-charcoal) and more frequent kitchen ventilation could reduce personal PM2.5 exposures. In summer, primary use of a gaseous fuel or electricity for cooking and reducing exposure to outdoor PM2.5 would likely have the greatest impacts on personal PM2.5 exposure.