Distribution, Source, and Ecological Risk of Heavy Metals in Sewage Irrigation of Taiyuan, Shanxi Province, China.

The pollution of agricultural soil by heavy metals is a significant environmental issue that has a serious impact on human health and food security. This study focused on investigating the presence of heavy metal pollution in sewage-irrigated soils in Taiyuan city. A total of 110 soil samples were analyzed for the presence of As, Hg, Cd, Pb, Cr, Cu and Zn. The results showed that the concentrations of these metals ranged from 0.06 to 26.74 mg/kg for As, 0.00 to 0.84 mg/kg for Hg, 0.03 to 0.69 mg/kg for Cd, 44.32 to 100.09 mg/kg for Pb, 9.85 to 42.19 mg/kg for Cr, 13.38 to 53.72 mg/kg for Cu, and 42.77 to 145.47 mg/kg for Zn. The average concentrations of these metals were found to be below the risk values specified in the "Soil environmental quality (GB15618-2018)", except for As and Cd in three sampling points in Xiaodian District. The heavy metal pollution in these areas can be attributed to various sources, such as industrial activities, the use of fertilizers and pesticides, and the irrigation process. According to the geo-accumulation index, the agricultural soil in the Taiyuan irrigation area was found to be uncontaminated by Zn, Cr, Cu, and As, and lightly contaminated by Cd, Hg, and Pb. The Nemerow Pollution Index indicated that the soil at all sampling points exhibited a slight level of pollution. Moreover, the ecological risk assessment indicated that all heavy metals posed a slight level of pollution. The findings of this study provide a scientific basis for the development of effective policies and measures for soil environmental protection and pollution control.

Forecast of peak infection and estimate of excess deaths in COVID-19 transmission and prevalence in Taiyuan City, 2022 to 2023.

In this paper, with the method of epidemic dynamics, we assess the spread and prevalence of COVID-19 after the policy adjustment of prevention and control measure in December 2022 in Taiyuan City in China, and estimate the excess population deaths caused by COVID-19. Based on the transmission mechanism of COVID-19 among individuals, a dynamic model with heterogeneous contacts is established to describe the change of control measures and the population's social behavior in Taiyuan city. The model is verified and simulated by basing on reported case data from November 8th to December 5th, 2022 in Taiyuan city and the statistical data of the questionnaire survey from December 1st to 23rd, 2022 in Neijiang city. Combining with reported numbers of permanent residents and deaths from 2017 to 2021 in Taiyuan city, we apply the dynamic model to estimate theoretical population of 2022 under the assumption that there is no effect of COVID-19. In addition, we carry out sensitivity analysis to determine the propagation character of the Omicron strain and the effect of the control measures. As a result of the study, it is concluded that after adjusting the epidemic policy on December 6th, 2022, three peaks of infection in Taiyuan are estimated to be from December 22nd to 31st, 2022, from May 10th to June 1st, 2023, and from September 5th to October 13th, 2023, and the corresponding daily peaks of new cases can reach 400 000, 44 000 and 22 000, respectively. By the end of 2022, excess deaths can range from 887 to 4887, and excess mortality rate can range from 3.06% to 14.82%. The threshold of the infectivity of the COVID-19 variant is estimated 0.0353, that is if the strain infectivity is above it, the epidemic cannot be control with the previous normalization measures.

[Content, Distribution, Source Analysis, and Risk Assessment of PAHs in Arable Soils of Taiyuan].

PAHs (polycyclic aromatic hydrocarbons) accumulated in arable soils have significant impacts on farmland quality and human health, which has attracted wide attention from scientists and the public. A total of 22 arable soil samples were collected from Taiyuan, an old industrial city, including three districts (industrial zones, hilly areas, and sewage irrigation area), and the contents of 21 PAHs were detected using the GC-MS method. The sources of PAHs in soils were analyzed using the diagnostic ratios (DRs) method and positive matrix factorization (PMF) model, and the soil health risks were analyzed using the incremental lifetime cancer risk (ILCR) model. The results indicated that the average concentrations of Σ21PAHs and Σ16PAHs in arable soils of Taiyuan were 934.6 ng·g-1 and 787.7 ng·g-1, respectively, which were lower than the soil pollution risk screening value of agricultural land stipulated in GB 15168-2018. 3-5 rings PAHs were the dominant components, accounting for~90% of the Σ21PAHs. Approximately 60% of sites in industrial zones, 13% in hilly areas, and 33% in the sewage irrigation area had high PAHs contents larger than 1000 ng·g-1. The spatial distribution of PAHs showed that more severe PAHs pollution in the soil occurred in industrial areas than that in the other two districts. The DRs suggested that the combustion of coals, bio-masses, and traffic emissions were the dominant sources for PAHs pollution in arable soils in Taiyuan. The simulation results of the PMF model indicated that the sources and contribution rates of PAHs in cultivated soils were coal and biomass burning sources (59%), traffic sources (22%), and coking sources (19%). The risk assessment confirmed that the arable soils in Taiyuan had high potential carcinogenic risks; thus, more attention should be paid to the PAHs pollutions in arable soils.

[On-line Measurement of Trace Elements in PM2.5 in Winter in Urban Taiyuan, China: Levels and Source Apportionment].

In order to better identify the sources of PM2.5 in Taiyuan, hourly concentrations of 13 trace elements (K, Ca, Ba, Cr, Mn, Fe, Cu, Ni, Zn, As, Se, Pb, and Sr) in PM2.5 were monitored at an urban site in Taiyuan from January 1 to 29, 2022. The pollution characteristics of trace elements were analyzed and sources were apportioned using positive matrix factorization (PMF). The results showed that the average concentration of 13 total trace elements was (3901.6±2611.2) ng·m-3, which accounted for (7.1±7.7)% of PM2.5. The three dominant elements were Fe[(1319.5±1003.5 ng·m-3)], Ca[(1181.0±1241.6 ng·m-3)], and K[(883.3±357.3 ng·m-3)]. The average concentrations of Cr(Ⅵ) (4.6 ng·m-3) and As (11.2 ng·m-3) exceeded the guideline values of the Chinese National Ambient Air Quality Standard (GB 3095-2012) and the World Health Organization. Fugitive dust, vehicle emissions, industry, stainless-steel production, biomass burning and waste incineration, residential coal combustion, and industrial coal combustion were identified by the PMF model, which accounted for 45.5%, 1.4%, 15.8%, 23.7%, 5.5%, and 8.1%, respectively, of the total elements.Compared with those during the stages of pollution development and dissipation, the contributions of industrial coal combustion, residential coal combustion, and biomass burning and waste incineration to the total elements during the pollution maintenance stage of the PM2.5 pollution episode increased significantly, contributing 11.8%, 7.1%, and 28.1%, respectively, of the total elements. These results could provide scientific references for the refined source apportionment of PM2.5 in other areas.

Remote Sensing Image Characteristics and Typical Area Analysis of Taiyuan Xishan Ecological Restoration Area.

The Taiyuan Xishan Ecological Restoration Zone is located in the west of Taiyuan City and belongs to the Xishan Coalfield. Due to the resource development activity of coal mining, which is caused by coal gangue accumulation, surface vegetation degradation, bare surfaces, and other phenomena, it is most common in this area. These have an impact on the surface ecology; however, after ecological restoration, the surface ecology has been greatly improved. There are many extraction models of vegetation coverage based on pixel dichotomology combined with multispectral vegetation index, but we believe that the combination of visible light vegetation index to construct models is relatively unexplored. The main problem of how to use the RGB image data in order to quickly and accurately extract vegetation coverage information is still under investigation and needs researchers' attention. In this paper, through selecting the vegetation coverage as the evaluation index of ecological restoration effect, a new RGB vegetation coverage CIVE calculation model is innovatively proposed to solve the above problem, and on the basis of this model, the vegetation cover change analysis is carried out in the Xishan ecological restoration area of Taiyuan. According to the analysis of vegetation coverage change, relevant paper data, and the characteristics of multiple historical remote sensing images, the ecological restoration area of Taiyuan Xishan is divided into six typical areas. Through empirical evaluation, we summarize and analyze these six typical areas, which can provide typical demonstration roles for other ecological restoration areas. Our findings suggest that the proposed CIVE model realizes the extraction of vegetation cover information and long-term series dynamic monitoring of vegetation coverage.

[Meteorological Characteristics, Influence Analysis and Prediction of PM2.5 Concentration in Taiyuan City].

Based on the pollutant concentration data of Taiyuan City from 2016 to 2020 and the surface meteorological data of the national benchmark meteorological observation station in the same period, the variation characteristics of PM2.5 concentration in Taiyuan City and the effects of meteorological conditions such as humidity, precipitation, wind, and mixing layer thickness on PM2.5 concentration were analyzed. At the same time, the causes of pollutant concentration changes were discussed, and the PM2.5 concentration prediction model based on the LSTM neural network was established. The results showed that the number of days of heavy pollution in Taiyuan City from 2016 to 2020 was the highest in winter, of which the maximum number of days in 2017 was 28 days. The PM2.5 concentration was generally high in autumn and winter and low in spring and summer. The PM2.5 concentration on weekends was higher than that on weekdays. The daily variation in PM2.5 concentration roughly presented a bimodal distribution, which appeared around 09:00 and 23:00 to 01:00 the following day. Except for relative humidity and winter temperature, other air pressure, wind speed, and PM concentration showed negative correlations in the four seasons. The pollution sources affecting the increase in PM2.5 concentration in Taiyuan City were mainly located in the NE-ENE-E direction, and the pollution in the northwest was not relatively apparent. In flood season, when the precipitation reached the level of moderate rain (rainfall ≥ 10 mm), it had an obvious effect on the reduction of PM2.5 concentration. The increase in atmospheric mixing layer height was very beneficial to the diffusion and dilution of PM2.5 in the vertical direction. The strong northwest air flow in winter, low relative humidity, high pressure control on the ground, and high height of the mixing layer belonged to the cluster most conducive to the reduction in PM2.5 concentration. Using the LSTM model for modeling, the R2 of PM2.5 concentration prediction was as high as 0.95, which was significantly better than that of the traditional tree model and linear regression model (R2<0.60). The residual of the prediction results was close to the normal distribution, of which the absolute error of 84.2% prediction results was less than 20 µg·m-3, and the MAE, MAPE, and RMSE of the model were 38.17, 17.19%, and 20.6, respectively.

[Analysis of Critical Source of Potentially Harmful Elements in Urban Road Dust During Winter in Taiyuan Based on Multiple Attribute Decision Making Method].

In order to analyze the critical sources of potential harmful elements (PHEs) in road dust from Taiyuan during winter, 40 road dust samples were collected. The contents of PHEs, including As, Cd, Pb, Ni, Cr, Cu, and Zn, in the road dust samples were measured using inductively coupled plasma mass spectrometry and atomic fluorescence spectrometry. The ecological risks and human health risks posed by dust PHEs were assessed using NIRI and a health risk evaluation model recommended by USEPA, respectively. The sources of dust PHEs were identified by using the combination of principal component analysis and positive matrix factorization (PMF); the total PHE contents and the ecological risks and human health risks posed by PHEs in dust were apportioned to the PHE sources based on the PMF results; subsequently, the critical source of dust PHEs was determined using the multiple attribute decision making method (MADM). The results demonstrated that: 1 the average concentrations of As, Cd, Pb, Ni, Cr, Cu, and Zn were 17.92, 0.32, 69.10, 30.06, 107.74, 73.37, and 268.49 mg·kg-1, respectively, which were higher than the corresponding background values of soil in Taiyuan, indicating that the PHEs had accumulated in road dust; the mean value of NIRI was 63.86, demonstrating that PHEs in dust posed moderate risks, and the dust PHEs pollution was controllable. 2 Human health risk assessment indicated that exposure to PHEs in dust did not pose serious non-carcinogenic or carcinogenic risks. Ingestion was the most important pathway for exposure to PHEs in road dust that damages human health, and As and Cr have been found to pose the most risks among the seven PHEs. 3 The present study found three main sources of PHEs measured in the dust: natural, traffic, and industrial, which accounted for 35.95%, 40.25%, and 23.82% of the total concentrations of PHEs, respectively. 4 Industrial emissions contributed the least to the total PHEs contents in dust; however, the PHEs released from industrial sources caused relatively high risks, with the results of MADM indicating that industrial sources were the most critical source for dust PHEs. Our results indicated that the critical source identification of PHEs, which was determined to be the most pernicious source, could provide reference for subsequent pollution source control.

Research on the Equity and Influencing Factors of Medical and Health Resources Allocation in the Context of COVID-19: A Case of Taiyuan, China.

COVID-19 has killed millions of people worldwide. As a result, medical and health resources continue to be strained, posing a great threat to people's safety and economic and social development. This paper built the index system of influencing factors of medical and health resources containing the economy, population and society, and then classified Taiyuan into three types of regions by cluster analysis. The Gini coefficient, Theil index and agglomeration degree were then used to analyze the spatial distribution of medical and health resources allocation, and its influencing factors were studied by grey relational analysis. It was found that the population allocation of medical and health resources in Taiyuan was better than area allocation. Population has the greatest influence on the allocation of medical and health resources, followed by society and the economy. The more developed the regional economy, the more diversified the main influencing factors, and the more adjustment and control choices of medical and health resources allocation. Suggestions for optimal allocation were put forward in order to fully utilize the limited medical and health resources, effectively respond to the epidemic needs, promote the sustainable development of resources, protect the health of residents, and improve social benefits.

[Characteristics of Heavy Metal Pollution and Ecological Risk Evaluation of Indoor Dust from Urban and Rural Areas in Taiyuan City During the Heating Season].

The presence of heavy metals in indoor dust is a world-wide concern owing to its negative impact on humans. In this study, we collected indoor dust samples from urban and rural residential areas during the heating season in Taiyuan City. We then identified the concentrations of 11 heavy metals (Cd, Co, Cr, Pb, Mn, Ni, Cu, Zn, V, As, and Hg) using inductively coupled plasma-mass spectrometry. Based on the concentrations, we categorized the pollution levels of indoor dust using the geo-accumulation index and the pollution load index. We further identified the sources of heavy metals using the enrichment factor and principal component analysis. Finally, we evaluated the potential ecological risks of heavy metals via the potential ecological index. The results illustrated that ① with the exception of Co, Mn, and V, the mean concentrations of Cd, Cr, Cu, Ni, Pb, As, Zn, and Hg in indoor dust were higher than the soil background values of Shanxi Province. There was a significant difference (P<0.05) in the concentrations of Co, Cr, Cu, Mn, Ni, and Hg between the urban and rural areas. ② Overall, the pollution degree of heavy metals in indoor dust was identified as moderate in the urban area of Taiyuan City, but slight in the rural area. The indoor dust sample in the urban area was not contaminated by Co, Mn, and V. However, it was slightly polluted by As, Ni, and Hg. In addition, it was close to moderately polluted by Cd, Cr, Cu, Pb, and Zn. In the rural area, the pollution degrees of all the metals, except for Hg and V, in indoor dust were lower than those in the urban area. ③ The As, Cd, Cu, Pb, Zn, and Hg in indoor dust for both urban and rural areas might have mainly originated from anthropogenic sources. The pollution sources were mainly transportation and industry in the urban area and coal combustion and indoor smoking in the rural area. The Co, Cr, Mn, Ni, and V in indoor dust in Taiyuan City might have mainly originated from natural sources. ④ The ecological risk of heavy metal pollution in indoor dust for both the urban and rural areas of Taiyuan City was relatively high, with integrated ecological risk indexes of 359.43 and 471.02 in the urban and rural areas, respectively. In addition, Cd and Hg were the largest contributors.

[Characteristics, Transportation, Pathways, and Potential Sources of Air Pollution During Autumn and Winter in Taiyuan].

Because of the atmospheric regional transmission, the air quality in Taiyuan is susceptible to air pollution from the surrounding areas. The annual and seasons air pollution characteristics of Taiyuan from 2014 to 2018 were analyzed using the environmental air quality index (AQI), the hourly backward trajectories in autumn and winter of 2014-2017 were calculated using the HYSPLIT model. The results showed that the air pollution situation in Taiyuan is not optimistic. There was a large fluctuation in the number of good days from 2014 to 2018, especially in the compliance rate of air quality, which varied from 64% to less than 50% over the past two years. However, the proportion of good days gradually increased in autumn and winter, exceeding 50% in 2018, and the trend in air quality improvement was obvious. The results also showed that air pollution may be more serious in spring and summer. Pollution types changed; whether annual or autumn and winter the days, PM2.5 as the main pollutant decreased significantly and the days with PM10 increased significantly in autumn and winter. Based on the backward trajectory model and it combination with the AQI, using Taiyuan as the starting point, the backward 72 hour trajectory from 00:00 on September 1, 2014 to 23:00 on December 31,2017 was calculated. The trajectory clustering analysis method, the potential source contribution factor weights (PSCF), and the concentration of the trajectory analysis (CWT) were used to discuss the source of contaminants in Taiyuan. The results showed that the simulated track after a clustering analysis could be divided into 8 categories, 53% of the trajectories come from the western region, 21% from the northwest, 12% from the southwest, and 14% from the east in autumn and winter of 2014-2017. The southwest trajectory was the main trajectory for the transportation of foreign pollutants into Taiyuan, and it has a significant impact on Taiyuan's air quality. PSCF and CWT analysis showed that the major potential sources affecting Taiyuan's air quality were mainly located in Fenwei plain, i. e., Hanzhong, Xi'an in Shaanxi Province, and Lvliang and Linfen in Shanxi Province. Establishing a joint prevention and control mechanism in the Fenwei plain and its surrounding areas would be of great significance for controlling pollution in the area.

Hydrogeochemical Characteristics and Water Quality Evaluation of Carboniferous Taiyuan Formation Limestone Water in Sulin Mining Area in Northern Anhui, China.

The Taiyuan formation limestone water in the Huaibei coalfield is not only the water source for coal mining, but also the water source for industry and agriculture in mining areas. Its hydrogeochemical characteristics and water quality are generally concerning. In this paper, conventional ion tests were carried out on the Taiyuan formation limestone water of 16 coal mines in the Sunan and Linhuan mining areas of the Huaibei coalfield. Piper trigram, Gibbs diagram and an ion scale coefficient map were used to analyze the hydrogeochemical characteristics of the Taiyuan formation limestone water. The water quality was evaluated in a fuzzy comprehensive manner. The results show that the main cation and anion contents in the Taiyuan formation limestone water were Na+ > Mg2+ > Ca2+ > K+, SO42- > HCO3- > Cl-. There were differences in the hydrogeochemical types of the Taiyuan formation limestone water in the two mining areas; HCO3-Na type water was dominant in the Sunan mining area and SO4·Cl-Na type water was dominant in the Linhuan mining area. The chemical composition of the Taiyuan formation limestone water is mainly affected by the weathering of the rock and is related to the dissolution of the evaporated salt and the weathering of the silicate. The fuzzy comprehensive evaluation results show that the V-type water accounts for a large proportion of the Taiyuan formation limestone water in the study area and the water quality is poor. This study provides a basis for the development and utilization of the Taiyuan formation limestone water and water environmental protection in the future.

[Chemical Composition Characteristics and Source Apportionment of PM2.5 During Winter in Taiyuan].

To study the characteristics and sources of PM2.5 pollution in Taiyuan urban area in winter, PM2.5 and its chemical components (water-soluble ions, carbon components, and trace elements) and gaseous pollutants (SO2, NO2) were monitored by online instruments in January 2017. Combined with meteorological data, the characteristics of PM2.5 and its chemical components were analyzed. Also, source apportionment of PM2.5 was conducted by using positive matrix factorization (PMF). The results showed that the mean mass concentration of PM2.5 on polluted days (239.92 µg·m-3) was 5.70 times as much as that on clean days. The concentrations of the main chemical components of PM2.5 on polluted days, SO42-, NO3-, NH4+, Cl-, OC, and EC, were 7.04, 5.76, 6.51, 5.62, 4.06, and 4.70 times their respective values on clean days. The sulfur oxidation ratios (SOR) and the nitrogen oxidation ratios (NOR) on polluted days were 0.12 and 0.19, respectively, which were higher than those in clean days, indicating that secondary transformation was more significant on polluted days. The results of the PMF source apportionment showed that the contributions of secondary sources (35.06%), coal combustion (30.19%), and vehicle emissions (24.25%) were higher on polluted days than on clean days, with increases of 18.03%, 7.39% and 2.10%, respectively. Thus, air pollution control strategies should pay more attention to controlling secondary source precursors on the basis of controlling the primary emission sources on polluted days.

Study of satisfaction and influencing factors of medical insurance for urban residents′in Taiyuan city / 中华医院管理杂志

Objective To learn the satisfaction and influencing factors of medical insurance for urban residents in Taiyuan city.Methods The multi-stage random sampling method was used to survey the satisfaction of medical insurance for urban residents so covered in 4 districts of Taiyuan city. The questionnaire covered basic personal information, and comments of the residents on the three dimensions of medical insurance regarding the stakeholders. The data solicited were subject to descriptive analysis, Kruskal-Wallis test and ordered multi-class logistic regression analysis. Results The rate of overall satisfaction of urban residents′ medical insurance in Taiyuan city was 44.6% , that of average satisfaction was 48.3% , and that of dissatisfaction was 7.1%.For residents of different family size and physical health status, the differences of their satisfaction were statistically different(P<0.05).Ordered multi-class logistic regression analysis showed that the proportion of reimbursement, the scope of drug treatment and the efficiency of treatment were top factors affecting their satisfaction ( OR > 1 ). Conclusions The rate of overall satisfaction of medical insurance by urban residents in Taiyuan city is low. To improve their satisfaction, it is important to increase the proportion of reimbursement, expand the scope of reimbursement for diagnosis and treatment along with drugs, simplify the reimbursement procedures, and improve the service attitude of the service agencies.

[Characteristics and Sources of Dissolved Heavy Metals in Summer Precipitation of Taiyuan City, China].

To investigate the characteristics and sources of dissolved heavy metals in precipitation of Taiyuan, 61 precipitation samples were collected using an automated dry and wet sampler from 2013 to 2015 during summertime. The concentrations of 12 dissolved heavy metals were detected using ICP-MS, and wet deposition fluxes and sources were analyzed. The results showed that the pH ranged from 4.34 to 7.95, with a volume-weighted mean of 5.37. The mean concentration of the dissolved heavy metals was 236.931 µg·L-1, with a range of 66.324 to 1029.212 µg·L-1. Zn and Fe were the major components, together accounting for 53.39% of the total concentrations. The wet deposition fluxes of the 12 dissolved heavy metals reached 1.735 mg·(m2·d)-1. The enrichment factors of Ba, Cu, Sr, Zn, As, Cd, and Pb were all in excess of 100, suggesting that these metals were seriously influenced by anthropogenic activities. Results from positive matrix factorization (PMF) indicated that steel smelting emissions, coal combustion, vehicle emissions, and crustal dusts were the major sources of heavy metals in the precipitation of Taiyuan City, with average contributions of 38.34%, 23.06%, 20.45%, and 18.15%, respectively. According to backward trajectory analysis, air masses from the southwest and southeast directions contributed the most to precipitation during summer in Taiyuan, with percentages of 38 and 35, respectively. The southern industrial areas located in the Yuncheng-Linfen-Jinzhong and Jincheng-Changzhi-Jinzhong regions should be paid more attention.

[Characteristics of Key Size Spectrum of PM2.5 Affecting Winter Haze Pollution in Taiyuan].

PM2.5 is generally considered as a main pollutant causing the formation of haze. Based on meteorological parameters, aerosol distribution, and PM monitoring data in Taiyuan during November and December 2016, the characteristics of the key size spectrum of PM2.5 affecting haze were discussed. During the observation period, haze was frequent and serious. Heavy haze time accounts for 25.35% of the total haze time. Haze events occurred frequently when the relative humidity was greater than 80% and wind speed was less than 1.5 m·s-1, especially for severe haze. Mild and moderate level haze occurred frequently when the relative humidity was less than 80% and greater than 40% and when wind speed was less than 1.5 m·s-1. Slight haze mainly occurred when the relative humidity was 20%-40% and the wind speed was 1.25-2.55 m·s-1. The average mass concentration of PM2.5 was 209.45 µg·m-3, which was three times the level during non-haze events. With an increase in the haze level, the mass concentration of PM2.5 and the ratio of PM2.5/PM10 increased. PM1 was the key particle size affecting haze in the low humidity environment. PM0.5 was the key particle size that affects slight haze, mild haze, and moderate haze in the high humidity environment, while PM1 was the key particle size that affects heavy haze. The contribution of surface concentration to visibility decreased with high humidity, but the particle size increased by moisture absorption leading to an increase in the extinction efficiency factor, which compensated for the lack of surface concentration. The increase in the particle size parameter was an important factor for PM2.5 affecting the haze pollution with high humidity.

Distribution of metal and metalloid elements in human scalp hair in Taiyuan, China.

This study investigated the levels of metal and metalloid elements (As, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Ni, Pb, and Zn) in scalp hair samples collected from 161 people of different age and gender groups living in the six districts of Taiyuan, an industrial city with rich coal reserve in Shanxi province in China. Levels of most elements in the hair were high in the 26-40 age groups and increased with the length of residence. Calcium, Cr, Mg, Ni and Zn levels in the females' hair were significantly higher than those in the males' (p < 0.05). Element levels in the hair didn't have significantly differences between industrial and non-industrial districts because most of industry factories are in the upper wind position in Taiyuan, and contamination is prone to spread to non-industrial districts. The principal component analysis indicates that the main sources of these elements are mining activities, the neighboring stainless steel industry, and coal combustion. These results indicate that the industrial activities primarily contribute to the metal and metalloid pollution in Taiyuan, whereas numerous factors caused the metals accumulation in hair.

Comparison of Health Risk Assessments of Heavy Metals and As in Sewage Sludge from Wastewater Treatment Plants (WWTPs) for Adults and Children in the Urban District of Taiyuan, China.

Abstract: To compare the human health risk of heavy metals and As in sewage sludge between adults and children, samples were collected from five wastewater treatment plants (WWTPs) located in the urban district of Taiyuan, the capital of Shanxi. Heavy metals and As in sewage sludge can be ranked according to the mean concentration in the following order: Cu > Cr > Zn > Pb > As > Hg > Cd. Compared with the concentration limit set by different countries, the heavy metals contents in sewage sludge were all within the standard limits, except for the content of As, which was higher than the threshold limit established by Canada. A health risk assessment recommended by the United States Environmental Protection Agency (USEPA) was used to compare the non-cancer risk and cancer risk between adults and children. Based on the mean and 95% upper confidence limit (UCL) of the average daily dose (ADD), heavy metals and As can be ranked in the order of Cu > Cr > Zn > Pb > As > Hg > Cd for adults, and Cu > Cr > Zn > Pb > Hg > As > Cd for children. Moreover, results of ADDingest and ADDinhale indicated that ingestion was the main pathway for heavy metals and As exposure for both adults and children, and the sum of ADD implied that the exposure to all heavy metals and As for children was 8.65 and 9.93 times higher, respectively, than that for adults according to the mean and 95% UCL. For the non-carcinogenic risk, according to the hazard quotient (HQ), the risk of Cu, Hg and Cr was higher than the risk of Zn and Pb. The hazard index (HI) for adults was 0.144 and 0.208 for the mean and 95% UCL, which was less than the limit value of 1; for children, the HI was 1.26 and 2.25, which is higher than the limit value of 1. This result indicated that children had non-carcinogenic risk, but adults did not. Furthermore, ingestion was the main pathway for non-carcinogenic risk exposure by the HQingest and HQinhale. For the carcinogenic risk, Cd and As were classified as carcinogenic pollutants. The values of RISK for the mean and 95% UCL for adults and children all exceeded the limit value of 1 × 10-5, which implied that adults and children had a carcinogenic risk, and this risk was higher for children than for adults. The results of RISK for As and Cd implied that As was the main pollutant for carcinogenic risk. Moreover, the results of RISKingest and RISKinhale indicated that ingestion was the main pathway. Uncertainty analysis was performed, and the risk ranges of it were greater than certainty analysis, which implied that uncertainty analysis was more conservative than certainty analysis. A comparison of the non-carcinogenic risk and carcinogenic risk for adults and children indicated that children were more sensitive and vulnerable than adults when exposed to the same pollutant in the environment.

Clearance capacity of the atmosphere: the reason that the number of haze days reaches a ceiling.

China has experienced rapid development in the past 30 years but, alongside and associated with this growth, increased levels of pollution too. However, despite the continued increase in emissions of haze-forming aerosols in the twenty-first century, the annual number of haze days in some megacities has not risen in tandem. Various mechanisms have been proposed for "city dimming", but the cause of the hiatus remains unclear. We found that the number of haze days in Taiyuan experienced a sharp increase during 1980-1998, with a growth rate 51.6 days/10a, and then exhibited fluctuating variation around a stable high level from 1998 to 2014, while at the same time the average visibility during haze days started to decrease. We present a novel method to explain the long-term variation in the number of haze days via a temporal-piecewise function of human activities and atmospheric cleaning processes: the number of haze days increases with the level of human activity before reaching the upper limit and then remains at a high level due to the restriction of a relatively stable number of strong cleaning days.

[Concentrations and Size Distributions of Water-soluble Inorganic Ions in Aerosol Particles in Taiyuan, Shanxi].

Size-resolved filter samples were collected in Taiyuan every other week from June 2012 to May 2014. The mass concentrations of water-soluble ions (Na+, NH4+, K+, Mg2+, Ca2+, F-, Cl-, NO3- and SO42-) were measured by ion chromatography. The results showed that the total concentrations of measured water-soluble ions were (15.39±9.91), (21.10±15.49) and (36.34±18.51) µg·m-3 in PM1.1, PM2.1 and PM9, respectively. In PM1.1 and PM2.1, secondary water-soluble ions (SO42-, NO3- and NH4+) comprised 87.59% and 86.30% of all water-soluble ions, respectively, while in PM9, SO42- and Ca2+ comprised 32.78% and 28.54% of all water-soluble ions, respectively. SO42- and NH4+ had higher concentrations in winter and summer, and lower in spring and autumn. NO3-, K+and Cl- presented similar seasonal variation with a descending order of winter >autumn >spring >summer, and Ca2+ and Mg2+ followed the sequence of spring >winter >autumn >summer. SO42- and NH4+ showed a unimodal size distribution and the peak in the fine mode shifted from 0.43-0.65 µm in spring and autumn to 0.65-1.1 µm in summer. NO3- showed a bimodal size distribution. NO3- and NH4+ were dominated by the fine mode peaking at 0.43-2.1 µm in winter, and NO3- was dominated by the coarse mode peaking at 4.7-5.8 µm in summer. K+, Na+and Cl- also showed a bimodal size distribution with the fine mode at 0.43-1.1 µm and the coarse mode at 4.7-5.8 µm. Ca2+, Mg2+ and F- were unimodal with the peak in the coarse mode of 4.7-5.8 µm. On heavily polluted days, the mass concentrations of secondary water-soluble ions and Cl- accumulated, and secondary water-soluble ions were unimodal with the peak in the fine mode of 1.1-2.1 µm. However, on clear days, secondary water-soluble ions showed a bimodal size distribution with the fine mode at 0.43-0.65 µm and the coarse mode at 4.7-5.8 µm. The peak of secondary water-soluble ions in the fine mode shifted. PCA analysis showed that the sources of water-soluble ions were dominated by the secondary formation, coal combustion, industrial emission, biomass burning, and soil particles or falling dust.

[Interannual Variations of Soil Respiration and Its Temperature Sensitivity in an Orchard in Jinci Region of Taiyuan City].

Jinci area of Taiyuan city is a former hometown of rice, and with the cutoff of the Jinci spring the land use in the area changed fundamentally from original paddy rice to corn or orchard use. So it is very important to investigate soil respiration after land use change and to analyze the relationship between soil respiration (Rs) and soil temperature (Ts) and soil water content (SWC), and to estimate soil carbon dioxide efflux in the region. For this purpose, we measured Rs for seven years (2006 to 2012) with an interval of 1 to 3 times per month from March to December in a field originally for rice but now Chinese jujube, and analyzed seasonal, annual variations of Rs and relationships between Rs and both Ts and SWC. The results showed that the seasonal variations of Rs against day number of the year could be significantly fitted with a three-parameter Gaussian equation while there was no significant correlation between Ts and SWC. Significant exponential relationship between Rs and Ts over the season was found, but not with SWC. Interannual average estimation of soil efflux between March and December from the soil was (5.32±3.31) µmol·(m2·s)-1, and was equal to 1690.2 g·m-2 from the same period ranging from 1294 to 2006 g·m-2. No significant difference in annual efflux was found between the years. The sensitivity of Rs to Ts, Q10 value, ranged from 1.54-2.20, 1.68-2.48 and 1.82-2.46, respectively, for the Ts measurement at 5, 10 and 15 cm depths. The Rs at 10℃, R10, ranged from 2.37 to 2.81, 2.43 to 3.13 and 2.59 to 3.47µmol·(m2·s)-1, respectively, for the Ts measurement at 5, 10 and 15 cm depths. Both the Q10 and R10 increased with increasing Ts measurement depth. In comparison with the fitted one-variable of temperature model, the two-variable model combining both the Ts and SWC together could be well used to predict Rs over the season. Our research results can bear important implications for the study of CO2 efflux in the region and similar regions.