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The rapid socio-economic development and urbanization in China have led to a decline in air quality. Therefore, the spatial and temporal distribution patterns of urban air pollution, as well as its formation mechanisms and influencing factors, have become important areas of research in atmospheric environment studies. This paper focuses on nine monitoring sites in Nanjing, where concentration data for six air pollutants and vegetation index data were collected from 2013 to 2021. The objective of this study is to investigate the changes in air pollutants and vegetation index over time and space, as well as their relationship with each other, and to assess the social and environmental impacts of air pollution. The findings reveal a spatial distribution pattern of air pollution in Nanjing that exhibits significant variability, with pollutant concentrations decreasing from the city center towards the surrounding areas. Notably, the main urban area has lower air quality compared to the peripheral regions. The results obtained from best-fit linear regression models and correlation heatmaps demonstrate a strong correlation (coefficient of determination, R2 > 0.5) between the normalized difference vegetation index (NDVI) and pollutants such as SO2, NO2, PM2.5, PM10, and O3 within a radial distance of 2 km from the air pollutant monitoring sites. These findings indicate that NDVI can be an effective indicator for assessing the distribution and concentrations of air pollutants. Negative correlations between NDVI and socio-economic indicators are observed under relatively consistent natural conditions, including climate and terrain. Therefore, the spatiotemporal distribution patterns of NDVI can provide valuable insights not only into socio-economic growth but also into the levels and locations of air pollution concentrations. [ABSTRACT FROM AUTHOR]

Accurate prediction of PM2.5 concentration is one of the key tasks of air pollution assessment, early warning, and treatment. In this paper, four monitoring sites were arranged in Jiangbei New District of Nanjing City, China. The environmental parameters such as PM2.5/PM10 concentration, temperature, and humidity were monitored from January to February 2020. A gated recurrent unit (GRU) network based on the PM2.5 concentration prediction model was established to predict PM2.5 concentration. The mean relative error (MRE), root mean square error (RMSE), and Pearson correlation coefficient were selected as the evaluation criteria for the accuracy of the GRU model. The data set was divided into a training set, a test set and a validation set at a ratio of 7:2:1, and the GRU model was used to predict the hourly value of PM2.5 concentration in the next week. The prediction results show that the Pearson correlation coefficients between the predicted values and the monitored values of the four monitoring sites have reached more than 0.9, reflecting a strong correlation. The relative average errors are around 10%. The GRU model prediction of NJAU (Nanjing Agricultural University)-Pukou Campus Site is the most accurate, and the correlation coefficient, MRE, and RMSE are 0.970, 7.85%, and 9.6049, respectively, reflecting the good prediction performance of the model. Therefore, this research supports the prediction of air quality in different cities and regions, so people can take protective measures in advance and reduce the damage caused by air pollution to human bodies. [ABSTRACT FROM AUTHOR]

In this paper, we present long-term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground-based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO vertical column densities (VCDs) are used to validate ozone monitoring instrument (OMI) satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. However, OMI observations are on average a factor of 3 lower than the MAX-DOAS measurements. Replacing the a priori NO2 profiles by the MAX-DOAS profiles in the OMI NO2 VCD retrieval would increase the OMI NO2 VCDs by ∼30 % with correlation nearly unchanged. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. An age-weighted backward-propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward-propagated HCHO data do not show a strong spatial correlation with the OMI HCHO observations. The result shows that the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants. The MAX-DOAS data are also used to evaluate the effectiveness of air pollution control measures implemented during the Youth Olympic Games 2014. The MAX-DOAS data show a significant reduction of ambient aerosol, NO2 and HCHO (30 %–50 %) during the Youth Olympic Games. Our results provide a better understanding of the transportation and sources of pollutants over the Yangtze River Delta as well as the effect of emission control measures during large international events, which are important for the future design of air pollution control policies. [ABSTRACT FROM AUTHOR]

Human activities are a key driver of air pollution, so it is hardly surprising that celebrations affect air quality. The use of fireworks contributes to high particulate concentrations in many parts of the world, with the Chinese Lunar New Year (spring festival) particularly noticeable, as firecrackers are traditionally used to drive off evil spirits. Fireworks lead to short-term peaks in the concentration of PM10, PM2.5 and SO. Regulatory actions that restrict the use of fireworks have been evident in China since the 1990s. This paper investigates the particulate concentrations in nine Chinese cities (Beijing, Chengdu, Chongqing, Tianjin, Xi'an, Nanjing, Shanghai, Guangzhou and Shenzhen, along with Hong Kong (a Special Administrative Region) and Taipei and Kaohsiung (Taiwan) with a particular focus on the celebrations of 2015. Extremely high concentrations of particulate matter were observed, with some sites revealing peak PM10 concentrations in excess of 1000 μg m in the early hours of the New Year. In Beijing, Tianjin and Chongqing, the activities caused high particulate matter concentrations at most sites throughout the city. These peaks in particulate load in the early hours of Chinese New Year do not appear to be closely related to meteorological parameters. However, in cities where fireworks appear to be better regulated, there are fewer sharp pollution peaks just after midnight, although lowered air quality can still be found in the outer parts of some cities, remote from regulatory pressures. A few cities seem to have been effective at reducing the impact of the celebrations on air quality, with Nanjing a recent example. An increasing focus on light displays and electric lanterns also seems to offer a sense of celebration with much reduced impacts on air quality. [ABSTRACT FROM AUTHOR]

In post-reform China, rapid motorisation causes various problems like traffic congestion, diminishing road safety and air pollution. Adequate policies necessitate an understanding of the forces behind changing mode choices, but the rapidly developing literature is not complete yet. This paper aims to help fill that gap with an analysis of mode choice for commuting and shopping-leisure trips in Nanjing. Using the Nanjing Residents Travel Survey, we find that models with the same independent variables explain mode choice in Nanjing better than in other cities in the world. Comparatively, members of 'adult families' use public transport and walking more often than the private car and bicycle. And inhabitants of danwei neighbourhoods walk more often than residents in commodity housing estates. These conclusions suggest that ongoing socio-spatial transformations will push mode choice in China further towards private car use. [ABSTRACT FROM AUTHOR]

Accurate forecasts of fog and visibility are very important to air and high way traffic, and are still a big challenge. A 1D fog model (PAFOG) is coupled to MM5 by obtaining the initial and boundary conditions (IC/BC) and some other necessary input parameters from MM5. Thus, PAFOG can be run for any area of interest. On the other hand, MM5 itself can be used to simulate fog events over a large domain. This paper presents evaluations of the fog predictability of these two systems for December of 2006 and December of 2007, with nine regional fog events observed in a field experiment, as well as over a large domain in eastern China. Among the simulations of the nine fog events by the two systems, two cases were investigated in detail. Daily results of ground level meteorology were validated against the routine observations at the CMA observational network. Daily fog occurrences for the two study periods was validated in Nanjing. General performance of the two models for the nine fog cases are presented by comparing with routine and field observational data. The results of MM5 and PAFOG for two typical fog cases are verified in detail against field observations. The verifications demonstrated that all methods tended to overestimate fog occurrence, especially for near-fog cases. In terms of TS/ETS, the LWC-only threshold with MM5 showed the best performance, while PAFOG showed the worst. MM5 performed better for advection-radiation fog than for radiation fog, and PAFOG could be an alternative tool for forecasting radiation fogs. PAFOG did show advantages over MM5 on the fog dissipation time. The performance of PAFOG highly depended on the quality of MM5 output. The sensitive runs of PAFOG with different IC/BC showed the capability of using MM5 output to run the 1D model and the high sensitivity of PAFOG on cloud cover. Future works should intensify the study of how to improve the quality of input data (e.g. cloud cover, advection, large scale subsidence) for the 1D model, particularly how to eliminate near-fog case in fog forecasting. [ABSTRACT FROM AUTHOR]

Urban plants have been proven to mitigate ambient particulate matter (PM), which can benefit urban planners in their attempts to control urban air pollution. In this study, PM depositions on the leaves of 8 tree species were quantitatively analysed in 7 functional areas of the city of Nanjing, China, over the course of one year. The results demonstrated that leaf PM included different particle size fractions (PM10 and PM2.5), and differed among seasons and species. The highest amounts of total PM, PM10, and PM2.5 were found in the industrial area, and the mean values were 80.24 μg/cm2, 52.14 μg/cm2, and 15.51 μg/cm2, respectively, and the highest accumulation of total PM (60.65 μg/cm2), PM10 (37.29 μg/cm2), and PM2.5 (11.23 μg/cm2) occurred in winter. Significant differences were found between the tree species tested. Cedrus deodara exhibited high amounts of the total PM, PM10, and PM2.5 accumulations. This study examined the mass and quantity distribution of PM among tree species, and identified the particles combined with a scanning electron microscope (SEM). In terms of particle mass, 48% of the identified particles had a diameter of 10 μm, and only 18.3% of them had a diameter of 2.5 μm. In terms of particle number, the results indicated that 73% of them had a diameter of 2.5 μm, and only 5.5% of them had a diameter of 10 μm. To test the relationship between leaf traits and PM2.5 accumulation, results showed that stomata size, density, and hair were significantly related to the PM2.5 capture quantity. As far as we know, this is the first paper to present the mass and quantity distribution of the PM of different tree species in Nanjing. The results not only give comprehensive insights into the dust-retaining capability of tree species but also offer a selection of species for urban green areas where the goal is to mitigate urban airborne PM. [ABSTRACT FROM AUTHOR]

Organic aerosols are harmful to the environment because of their impact on air quality and visibility. They have serious effects not only on living beings and ecosystems because of their biological toxicity, but they also have an indirect effect on regional climate change as cloud condensation nuclei and radiation force. Many measures have been applied to decrease air pollution. Although the air quality has greatly improved, the standard of the World Health Organization (WHO) is far from being met at present. In this study, fine particulates were collected in Nanjing throughout 2019, and high-performance liquid chromatography–electrospray ion–mass spectrometry/mass spectrometry (HPLC-ESI-MS/MS) was carried out to determine 14 organic acids, 10 nitrated phenols, 1 aldehyde, and 1 ketone in aerosol samples. In this study, we further determined the changes in the pollutants in Nanjing in recent years compared to previous studies and characterized more kinds of species in the air. We found that different kinds of nitrated phenols showed similar trends of being abundant in winter and substituted in spring, autumn, and summer. 4-Nitrophenol was the most abundant species (2.83 ng m−3) among the nitrated phenols. p-Coumaric acid presented the highest level in summer with an average concentration of 1.55 ng m−3, indicating that grass burning was significant in summer, possibly due to wheat stalk and perennial ryegrass burning. The positive matrix fraction (PMF) model was applied to identify the sources of aerosols in Nanjing, including coal burning, grass burning, softwood burning, hardwood burning, anthropogenic secondary organic aerosols (SOAs), and biogenic SOAs. Coal burning and softwood burning contributed much more to the total determined species with values of 20.3% and 18.2%, respectively. Anthropogenic SOAs contributed 17.1%, and hardwood burning contributed 16.7%. The contribution of biogenic SOAs was 15%, and the grass-burning source contribution was the lowest, with 12.6%. With consideration of the large contribution from anthropogenic combustion activities, more strict measures are required to reduce emission pollutants in the future. [ABSTRACT FROM AUTHOR]

Despite the large number of domestic inland river vessels in China, information on inland ship emissions is very limited, since legislation for shipping emission control is limited and there is no monitoring infrastructure. Taking the Yangtze River in the region of Nanjing as a research area, we compiled a ship emission inventory based on real-time information received from automatic identification system (AIS) signals combined with ship-related data provided by the China Classification Society (CCS) database. The total ship emissions we derived for the Jiangsu section of the Yangtze River from September 2018 to August 2019 for NO x , SO 2 , PM 10 and PM 2.5 were 83.5, 0.04, 0.006 and 0.005 kt yr -1 , respectively. This ship emission inventory we constructed was compared with the Multi-resolution Emission Inventory for China (MEIC), the Shipping Emission Inventory Model (SEIM) and the satellite-derived emissions using the Daily Emissions Constrained by Satellite Observations (DECSO) algorithm. The results show a consistent spatial distribution, with riverine cities having high NO x pollution. With this comparison we analyzed the relative impact of ship emissions on densely populated regions along the river. Inland ship emissions of NO x are shown to contribute significantly, accounting for at least 40 % of air pollution close to the river. [ABSTRACT FROM AUTHOR]

To avoid the spread of COVID-19, China has implemented strict lockdown policies and control measures, resulting in a dramatic decrease in air pollution and improved air quality. In this study, the air quality model WRF-Chem and the latest MEIC2019 and MEIC2020 anthropogenic emission inventories were used to simulate the air quality during the COVID-19 lockdown in 2020 and the same period in 2019. By designing different emission scenarios, this study explored the impact of the COVID-19 lockdown on the concentration of air pollutants emitted by different sectors (industrial sector and transportation sector) in Nanjing for the first time. The results indicate that influenced by the COVID-19 lockdown policies, compared with the same period in 2019, the concentrations of PM2.5, PM10, and NO2 in Nanjing decreased by 15%, 17.1%, and 20.3%, respectively, while the concentration of O3 increased by 45.1% in comparison; the concentrations of PM2.5, PM10 and NO2 emitted by industrial sector decreased by 30.7%, 30.8% and 14.0% respectively; the concentrations of PM2.5, PM10 and NO2 emitted by transportation sector decreased by 15.6%, 15.7% and 26.2% respectively. The COVID-19 lockdown has a greater impact on the concentrations of PM2.5 and PM10 emitted by the industrial sector, while the impact on air pollutants emitted by the transportation sector is more reflected in the concentration of NO2. This study provides some theoretical basis for the treatment of air pollutants in different departments in Nanjing. [ABSTRACT FROM AUTHOR]

A special and unusual purple (magenta) haze episode was observed in Nanjing, China, at 17:00 on 22 December 2015. Many local and national news outlets reported this event. Based on an analysis of the pollution features and meteorological factors, including boundary layer characteristics, we concluded that this haze event was similar in most respects to other local haze episodes. We discuss the reasons and the possibilities about this rare color haze at the end of the paper. One way to attain a combination of blue and red light is to have the green wavelengths selectively absorbed, and this seems unlikely for typical atmospheric constituents. Another way involves pollution gases or particles together with small liquid-water drops, which need further confirmation. A third possibility is that the combination of transmitted red light from the sun and scattered blue light from above could produce a purple/magenta color in the sky. In general, further studies are required to assess the physical, chemical, and optical features of this purple haze in order to explain and predict this phenomenon in the future. [ABSTRACT FROM AUTHOR]

Atmospheric Aerosol Optical Depth (AOD), derived from polar-orbiting satellites, has shown potential in PM 2.5 predictions. However, this important source of data suffers from low temporal resolution. Recently, geostationary satellites provide AOD data in high temporal and spatial resolution. However, the feasibility of these data in PM 2.5 prediction needs further study. In this paper, we analyzed the impact of AOD derived from Himawari-8 in PM 2.5 predictions. Moreover, by combining wavelet, machine learning techniques, and minimum redundancy maximum relevance (mRMR), a novel hybrid model was proposed. The results showed that AOD missing rate over Yangtze River Delta region is the highest in Nanjing, Hefei, and Maanshan. In addition, missing rates are the lowest in winter and summer (∼80%). Moreover, we found that considering AOD, as an auxiliary variable in the model, could not improve the accuracy of PM 2.5 predictions, and in some cases decreased it slightly. In comparison with other models, our proposed hybrid model showed higher prediction accuracy, R2 is improved by 11.64% on average, and root mean square error, mean absolute error, and mean absolute percentage error is reduced by 26.82%, 27.24%, and 29.88% respectively. This research provides a general overview of the availability of Himawari-8 AOD data and its feasibility in PM 2.5 predictions. In addition, it evaluates different machine learning approaches in PM 2.5 predictions. Our proposed framework can be used in other regions to predict different air pollutants concentrations and can be used as an aid for air pollution controlling programs. [ABSTRACT FROM AUTHOR]

Studies on the vitality of urban residents' daily commuting and air pollution are scarce. Based on the cell phone mobile signaling data, urban air quality observation data, and urban transportation infrastructure environment data of Nanjing in 2019, and through the panel regression model and the standard deviation ellipse analysis (SDE) to measure the impact of air pollution on residents' daily traffic vitality, we construct the survey panel matrix data system with streets as spatial units. Through SDE and panel regression model analysis, we measured the restraining effect of air pollution on the traffic vitality. The scope of the traffic vitality area SDE was found to shrink as the air quality index (AQI) increases. The study found three main characteristics: (1) Under different transportation models and different location conditions, there are obvious differences in traffic vitality. The entire city presents a trend of "northeast-southwest" axial expansion in the spatial pattern of the traffic vitality. Compared with the urban core area, the traffic vitality of residents in the north-south areas of Nanjing's periphery has declined significantly. (2) The inhibitory effect of air pollution on public traffic vitality and self-driving traffic vitality are differences. Approximately one-tenth of traffic activities may be inhibited by air pollution. The weakening of traffic vitality greatly reduces the city's ability to attract and gather people, materials, and resources. (3) The inhibitory effect of air pollution on traffic vitality is heterogeneous under different transportation infrastructure environments. The higher the public transportation station density and public transportation frequency of the street, the more obvious the suppression effect of air pollution. The higher the parking density, station accessibility, road intersections density, and transportation facility diversity, the lower the suppression effect of air pollution. This study elucidates the relationship among air pollution, the transportation infrastructure environment, and the traffic vitality, and provides significant guidelines for optimizing the organization of elements in the transportation infrastructure environment, thereby mitigating the inhibitory effect of air pollution on traffic vitality. [ABSTRACT FROM AUTHOR]

Inorganic nitrate production is critical in atmospheric chemistry that reflects the oxidation capacity and the acidity of the atmosphere. Here we use the oxygen anomaly of nitrate (Δ17O( NO 3 − )) in high-time-resolved (3 h) aerosols to explore the chemical mechanisms of nitrate evolution in fine particles during the winter in Nanjing, a megacity of China. The continuous Δ17O( NO 3 − ) observation suggested the dominance of nocturnal chemistry (NO3 + HC/H2O and N2O5 + H2O/Cl−) in nitrate formation in the wintertime. Significant diurnal variations of nitrate formation pathways were found. The contribution of nocturnal chemistry increased at night and peaked (72%) at midnight. Particularly, nocturnal pathways became more important for the formation of nitrate in the process of air pollution aggravation. In contrast, the contribution of daytime chemistry (NO2 + OH/H2O) increased with the sunrise and showed a highest fraction (48%) around noon. The hydrolysis of N2O5 on particle surfaces played an important role in the daytime nitrate production on haze days. In addition, the reaction of NO2 with OH radicals was found to dominate the nitrate production after nitrate chemistry was reset by the precipitation events. These results suggest the importance of high-time-resolved observations of Δ17O( NO 3 − ) for exploring dynamic variations in reactive nitrogen chemistry. [ABSTRACT FROM AUTHOR]

Pneumonia is a major cause of childhood morbidity in China. Many studies of rural areas have found an association between pneumonia and air pollution from burning of bio-mass. The present study is of children living in urban, modern homes without burning of bio-mass. In order to investigate potential home risk factors associated with children’s pneumonia, China Child Home Health (CCHH) questionnaires were randomly distributed to parents of 6461 children in 23 kindergartens in all 11 districts of Nanjing, covering urban, suburban, and industrial areas. The 4014 valid questionnaires (response rate 65.7%) were returned and have been analyzed. The lifetime incidence of pneumonia in Nanjing children 1–8 years old is 26.7%. The incidence of croup, asthma and frequent common colds was strongly associated with pneumonia, as was a history of allergies in the family, and persons other than parents (for example grandparents or nanny) taking care of the child. Several home environmental factors, namely, dampness, lack of ventilation, using coal or natural gas (electricity as reference) for cooking, new furniture, and “modern” floor and wall covering materials were also significantly associated with pneumonia. The indoor environment typical of modern apartments in China was a risk factor for pneumonia among children. [ABSTRACT FROM AUTHOR]

Particulate matters with an aerodynamic diameter ≤1 μm (PM1) significantly increased mortality risk, and the effect of PM1 was even greater than that of PM2.5 (aerodynamic diameter ≤2.5 μm). But the quantitative impact of PM1 on life expectancy was unknown. We aim to examine the extent to which that people's life expectancy was shortened by PM1 and PM2.5. We obtained daily data on deaths, PM1 and PM2.5 records, and weather variables during 2016–2017 in Nanjing, China. Years of life lost (YLLs) were calculated by matching each decedent's age and sex to the Chinese life table. The fitted nonlinear dose-response associations of YLLs with PM1 and PM2.5 were estimated by utilizing a generalized additive model with a Gaussian link that controlled for confounding factors including meteorological variables, day of week, and long-term trend and seasonality. The effect estimates were presented as the YLLs when PM1 and PM2.5 concentrations fell in different ranges. Life expectancy losses attributable to PM1 and PM2.5 were calculated. Stratified analyses were also performed by age, sex, and death causes. Significant PM-YLL associations were observed, with greater increases in YLLs associated with PM1 (68.9 thousand). PM1 was estimated to reduce life expectancy, which was greater than PM2.5 (PM1: 1.67 years; PM2.5: 1.55 years). For PM1, greater years of loss in PM-related life expectancy were found in the female group, ≥65 years group, and cardiovascular disease group. Exposure to PM1 had a greater impact on life expectancy loss than did PM2.5. Constant efforts are urgently needed to control PM1 air pollution to improve people's longevity. [ABSTRACT FROM AUTHOR]

It is known that air pollution is harmful to creatures, though until now most of the human thermal comfort indices that existed were calculated only with meteorological conditions. Therefore, a new index - meteorology and environment comfort (MEC) - was given out in this paper that considers both meteorology and air pollution conditions and presents the comprehensive and synergistic effects of meteorological and air pollution. The meteorology and air pollution data were used to establish the influence function of the five air pollutants (PM 2.5 , PM 10 , O 3 , NO 2 , and SO 2) according to Fechner's law; then, we calculated the somatosensory temperature (ST, a class of human thermal comfort indices) and MEC values of five typical cities (Beijing, Xining, Nanjing, Kunming, and Guangzhou). The results showed average improvements of five cities on MEC as a new comprehensive human comfort index to new ST. In spring, the MEC comfort proportion fell by 29.25%. Besides, the extreme heat discomfort ratio in Nanjing and Kunming has increased over 20%. In summer, the comfort proportion fell 12.54%; the extreme heat discomfort proportion of Beijing increased 37.86% and Kunming increased 24.09%. Air pollution significantly raised discomfort stress in Beijing. In fall, the comfort proportion fell by 20.87%; and the extreme heat discomfort of Nanjing increased 23.67% caused by poor air quality. About winter, the comfort ratio decreased 12.72%, and the cold discomfort proportion of Nanjing increased 30.30%, signifying awful air quality in winter. Air pollution levels significantly affect the comfort levels in all seasons, which is more evident with good weather patterns. MEC can offer early warnings of extreme weather events and provide a basis for the better prevention and control of air pollution to protect human health basing on the predictions of meteorological and environmental impact factors. [Display omitted] • Both meteorological elements and air pollution would affect human health. • New ST shows Guangzhou is the most comfortable city and Nanjing is the worst. • MEC indicates Kunming is the most pleasant, followed by Guangzhou, Xining, Beijing, and Nanjing. • Comparing new ST and MEC, air pollution makes urban comfort levels worse. • MEC presents the comprehensive and synergistic effects of meteorological and air pollution. [ABSTRACT FROM AUTHOR]

Background: The correlation of unintentional injury mortality to rising temperatures found in several studies could result from changes in behavior that increases exposure to hazards or risk when exposed. Temperature, precipitation and air pollutants may contribute to symptoms and distractions that increase risk or avoidance behavior that reduces risk. This study examines data that allows estimates of the relation of daily maximum temperature, precipitation and ozone pollution to injury mortality risk, each corrected statistically for the correlation with the others. Methods: Daily data on unintentional injury deaths and exposures to temperature, precipitation and ozone in 9 cities in Jiangsu Province, China during 2015–2017 were analyzed using Poisson regression. The regression estimates were adjusted for weekends, holidays, an anomalous difference in death rates in Nanjing, and population size. Results: Non transport injury death risk increased substantially in relation to higher temperatures when temperatures were in the moderate range and even more so at temperatures 35 degrees (C) and higher. Transport deaths were related to increasing deaths when temperatures were low but the correlation reversed at higher temperatures. Deaths were lower on rainy days when temperatures were cool and moderate with the exception of non-transport injuries when temperatures were moderate. Higher ozone concentrations were associated with more deaths except when temperatures were low. Conclusions: The variations in deaths in relation to temperature, precipitation and ozone suggest that people are behaving differently or are in different environments when specific combinations of the predictor variables are prevalent, putting them at greater or less risk. More study of the behaviors and circumstances that result in injury under those conditions is needed. [ABSTRACT FROM AUTHOR]

An integrated winter field campaign was conducted to investigate the atmospheric boundary layer structure and PM2.5 concentration at three sites over the Yangtze River delta (YRD) in China: Shouxian (a rural area), a site in a northern suburb of Nanjing, and Dongshan (a residential area). Two temperature inversion layers and air pollution events occurred simultaneously from 30 to 31 December 2016, local time, over the YRD. It was found that the two inversion layers were related to the presence of a high pressure system, resulting in divergence in the upper boundary layer and radiative cooling near the ground at night. Dominated by agricultural and residential biomass burning, the surface emission sources from the Shouxian rural area were moderately strong. After the formation of the two inversions, the vertical distribution of PM2.5 concentration below the upper inversion layer was uniform as a result of thorough boundary layer mixing in the earlier hours. During nighttime at the Nanjing site, air pollutant plumes from nearby elevated point sources could not easily diffuse downward/upward between the two inversion layers, which led to a distinct peak in the PM2.5 concentration. At the Dongshan site, the emission sources were weak and the nighttime PM2.5 concentration above 100 m was high. The surface PM2.5 concentration gradually increased from early morning to noon, which was attributed to emissions related to the local residents. The results indicated that the vertical distribution of pollutants was affected by a combination of local emissions, vertical boundary layer structure, and horizontal and vertical transports. [ABSTRACT FROM AUTHOR]

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In order to make full use of national monitoring sites data, the variations of mass concentrations of PM2.5 and other criteria pollutants in Nanjing City were investigated on the basis of data from nine national monitoring sites. These monitoring sites provide 24 hr average data to evaluate the spatiotemporal variations of PM2.5 mass concentration. The characteristics of the annual, seasonal, monthly and hourly variations of PM2.5 mass concentrations were analysed. PM2.5 concentrations were higher in the winter months, yet lower in the summer and whole afternoon time, but became better and better during 2014-2016. Afterwards Pearson correlation coefficients were calculated between PM2.5 and other criteria pollutants. The correlation coefficients between PM2.5 and PM10 at 9 monitoring sites were more than or equal to 0.76, and were lower in spring while higher in winter, summer and fall. However, the correlation between PM2.5 and SO2, NO2, CO varied in four seasons with lower correlation in summer and higher correlation in winter, spring and fall. Through calculating hourly correlation coefficients between PM2.5 and PM10, SO2, NO2, the correlation coefficients between PM2.5 and PM10 were lower in the afternoon, on the contrary, the correlations of PM2.5 and SO2, NO2 were lower in the night-time and morning. The correlation curves of PM2.5 and O3 barely changed, which gives us the information that O3 was weakly correlated with PM2.5. The investigation of PM2.5 and other criteria pollutants may provide some implications for the key reasons leading to the regional high PM2.5 and lay the foundation for further research of PM2.5 control strategies in Nanjing. [ABSTRACT FROM AUTHOR]

In order to investigate the size distributions and seasonal variations of carbonaceous aerosols (organic carbon (OC) and elemental carbon (EC)), the carbonaceous species were collected in Nanjing, a typical industrial city located in Yangtze River Delta, China, in the summer, autumn, and winter of 2013 and spring of 2014, and then analyzed by using a 9-stage Anderson-type aerosol sampler and DRI Model 2001A Thermal/Optical Carbon Analyzer. OC, EC, secondary organic carbon (SOC), and primary organic carbon (POC) exhibited obvious seasonal variations, with the highest levels in winter (39.1±14.0, 5.7 ± 2.1, 23.6 ± 11.7, and 14.1 ± 5.7 µg⋅m-3, respectively) and the lowest levels in summer (20.6 ± 6.7, 3.3 ± 2.0, 12.2 ± 3.8 and 8.4 ± 4.1 µg⋅m-3, respectively), and were mainly centralized in PM1.1 in four seasons. The concentrations of OC in PM1.1 varied in the order of winter > autumn > spring > summer, while EC ranked in the order of autumn > winter > summer > spring. In the PM1.1-2.1 and PM2.1-10, the concentrations of OC and EC decreased in the sequence of winter > spring > autumn > summer. The size spectra of OC, EC, and SOC had bimodal distributions in four seasons, except for EC with four peaks in summer. The size spectra of POC varied greatly with seasons, exhibiting bimodal distribution in winter, trimodal distribution in spring and summer, and four peaks in autumn. The OC/EC ratios were 7.0, 6.3, 7.6, and 6.9 in spring, summer, autumn and winter, respectively, which demonstrated the abundance of secondary organic aerosols in Nanjing. The sources of carbonaceous aerosol varied significantly with seasons, and were dominated by vehicle exhaust, and coal and biomass burning in PM2.1, and dominated by dust, and coal and biomass burning in PM2.1-10. [ABSTRACT FROM AUTHOR]

Intensive field experiments focused on fog chemistry were carried out in the northern suburb of Nanjing during the winters of 2006 and 2007. Thirty-seven fog water samples were collected in nine fog events. Based on the chemical analysis results of those samples and the simultaneous measurements of air pollution gases and atmospheric aerosols, the chemical characteristics of fog water and their relations with air pollutants during fog evolution were investigated. The results revealed an average total inorganic ionic concentration TIC = 21.18 meq/L, and the top three ion concentrations were those of SO, NH and Ca (average concentrations 6.99, 5.95, 3.77 meq/L, respectively). However, the average pH value of fog water was 5.85, which is attributable to neutralization by basic ions (NH and Ca). The average TIC value of fog water measured in advection-radiation fog was around 2.2 times that in radiation fog, and the most abundant cation was NH in advection-radiation fog and Ca in radiation fog. In dense fog episodes, the concentration variations of primary inorganic pollution gases showed a 'V'-shaped pattern, while those of volatile organic compounds (VOCs) displayed a 'Λ'-shaped pattern. The dense fog acted as both the source and sink of atmospheric aerosol particles; fog processes enhanced particle formation, leading to the phenomenon that the aerosol concentration after fog dissipation was higher than that before the fog, and at the same time, mass concentration of PM reached the lowest value in the late stage of extremely dense fog episodes because of the progressive accumulated effect of wet deposition of large fog droplets. Both air pollution gases and aerosols loading controlled the ion compositions of fog water. The Ca in fog water originated from airborne particles, while SO and NH were from both heterogeneous production and soluble particulate species. [ABSTRACT FROM AUTHOR]

Transport emissions and street dust are important sources of summertime air pollution in urban centers. Street greening and buildings have an influence on the diffusion of air pollution from streets. For field measurements, many studies have analyzed the effect of street green space arrangement on the diffusion of air pollution, but these studies have neglected the patterns at the landscape scale. Other studies have analyzed the effects of the large scale of green space on air pollution, but the vertical distribution of street buildings and greening has rarely been considered. In this study, we analyzed the impact of the vertical distribution of urban street green space on summertime air pollution in urban centers on the urban scale for the first time by using a deep-learning method to extract the vertical distribution of street greening and buildings from street view image data. A total of 687,354 street view images were collected. The green index and building index were proposed to quantify the street greening and street buildings. The multilevel regression method was used to analyze the association between the street green index, building index and air pollution indexes. For the cases in this study, including the central urban areas of Beijing, Shanghai and Nanjing, our multilevel regressions results suggested that, in the central area of the city, the vertical distribution of street greening and buildings within a certain range of the monitoring site is association with the summertime air pollution index of the monitoring site. There was a significant negative association between the street greening and air pollution indexes (radius = 1–2 km, NO2, p = 0.042; radius = 3–4 km, AQI, p = 0.034; PM10, p = 0.028). The street length within a certain range of the monitoring site has a positive association with the air pollution indexes (radius = 1–2 km, AQI, p = 0.072; PM10, p = 0.062). With the increase of the distance between streets and the monitoring sites, the association between streets and air pollution indexes decreases. Our findings on the association between the vertical structure of street greening, street buildings and summertime air pollution in urban centers can support urban street planning. [ABSTRACT FROM AUTHOR]

Air pollution shows a generally decreasing trend from the north to the south in China since 2013 (GB3095-2012, the current standard for monitoring). However, an opposite observation was recorded in 2017, especially in winter. In this study, we collected monitoring data of six air pollutants in 2016 and 2017, from a northern city (Beijing) and a southern city (Nanjing) for comparison. As air pollution was highly dependent upon meteorological conditions, we further analyzed their relationships to explain this abnormal phenomenon. Seasonal averaged PM2.5, PM10, SO2, CO, and NO2 were negatively correlated with wind scale (WS) while 8-h O3 exhibited an opposite relationship. Relative humidity (RH) has opposite effects on the concentrations of different pollutants in Beijing and Nanjing. The 8-h O3 showed the closest positive correlation with temperature (T), which is due to its formation mechanism. In Beijing, decreased RH, together with more wind from northwest in winter, resulted in an improved air quality in 2017. In Nanjing, WS, RH, T, and wind direction fluctuated within a narrow range in each season, leading to relatively stable pollutant concentrations. These results suggest that meteorological conditions are important factors to evaluate the air quality and implement control measures. [ABSTRACT FROM AUTHOR]