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BackgroundAffected by concentration, composition, and population tolerance of air pollutants, the relationship between air pollutants and population health has regional differences. There is still a research gap in Guiyang.ObjectiveTo explore the short-term effects of air pollutant concentrations in low-pollution areas on the outpatient volume of respiratory diseases.MethodsSpearman correlation analysis was used to evaluate the correlation between air pollutants, meteorological factors, and respiratory outpatient volume from January 1, 2013 to December 31, 2020 in Guiyang City. A single pollutant distribution lag nonlinear model and a multi-pollutant interaction model were established based on Poisson distribution. A three-dimensional diagram was drawn to display the relationship between air pollutants and respiratory outpatient volume. Quantitative analysis was conducted on the attribution risk and lag effect of air pollutant concentration on outpatient volume of respiratory diseases in Guiyang City.ResultsThe results of the single pollutant model showed that fine particulate matter (PM2.5), nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2) elevated the outpatient volume of respiratory diseases. The maximum relative risk (RR) and 95%CI values of PM2.5, NO2,CO, and SO2 appeared on Day 2, 0, 5, and 6, respectively, which were 1.019 (1.015, 1.023), 1.146 (1.122, 1.171), 1.129 (1.116, 1.143), and 1.046(1.040, 1.052), respectively. For every quartile concentration increment of PM2.5, NO2, CO, or SO2, the outpatient volume of respiratory diseases increased by 0.943% (0.111%, 1.782%), 4.050% (3.573%, 4.529%), 0.595% (0.317%, 0.874%), or 0.667% (0.235%, 1.100%), respectively. The maximum RR (95%CI) of O3 was 1.015 (1.007, 1.023) and appeared on Day 0. The results of multi-pollutant model showed that PM2.5, NO2, CO, SO2, and O3 all elevated the outpatient volume of respiratory diseases. The maximum RR values of PM2.5, NO2, CO, SO2 and O3 appeared on Day 14, 0, 5, 7 and 0, respectively, which were 1.027 (1.021, 1.034), 1.213 (1.179, 1.248), 1.059 (1.043, 1.074), 1.016 (1.005, 1.026), and 1.024 (1.015, 1.033), respectively. Compared with the single pollutant model, the RR values of PM2.5, NO2, and O3 on the outpatient volume of respiratory diseases in the multi-pollutant model showed an upward trend, while the RR values of CO and SO2 in the multi-pollutant model showed a downward trend.ConclusionThe impact of low concentrations of PM2.5, NO2, CO, and SO2 on human health cannot be ignored.

BackgroundThe impact of atmospheric fine particulate matter (PM2.5) and ozone (O3) on the mortality of circulatory system diseases cannot be ignored. However, whether the interaction between PM2.5 and O3 can affect population health is rarely reported and requires study. ObjectiveTo investigate the individual and interactive impacts of atmospheric PM2.5 and O3 on the mortality of circulatory system diseases in the population of Ningxia region. MethodsThe data of 119647 deaths due to circulatory system diseases, daily average concentrations of atmospheric pollutants, and meteorological data in Ningxia from 2013 to 2020 were retrieved. PM2.5 was divided into low, medium, and high concentrations according to the primary and secondary national limits (35 and 75 μg·m−3) of the Ambient air quality standards. Similarly, O3 was divided into low, medium, and high concentrations according to the national limits (100 and 160 μg·m−3). Using a generalized additive mixed model based on quasi Poisson distribution, the impacts of atmospheric PM2.5 and O3 as well as their interaction on the mortality of circulatory system diseases were analyzed using the population data of Ningxia region. ResultsDuring the target period, males and the ≥ 65 year group accounted for larger proportions of deaths due to circulatory system diseases (55.47% and 79.87% respectively). The daily average concentration of PM2.5 (40.25 μg·m−3) exceeded the national primary limit. In the single pollution model, the highest cumulative lag effects for mortality from circulatory system diseases were PM2.5 exposure over previous 1 d (lag01) and O3 exposure for previous 2 d (lag02), and their excess risk (ER) values were 1.03% (95%CI: 0.67%, 1.40%) and 1.02% (95%CI: 0.57%, 1.50%), respectively. The results of concentration stratification analysis showed that the most significant risks of death from circulatory system diseases [ER (95%CI): 1.12% (0.32%, 1.92%) and 0.95% (0.13%, 1.79%) respectively] were found at medium PM2.5 and O3 concentrations. The interaction analysis revealed that under, a synergistic effect on the risk of death from circulatory system diseases was identified (relative excess risk due to interaction=3.08%, attributable proportion of interaction=2.90%, synergy index=1.89) when considering the coexistence of PM2.5 and O3 above the primary limit. As the concentrations of PM2.5 and O3 increased, the synergistic effect increased the risk of death from circulatory system diseases in the general population, men, women, and the ≥ 65 years group. ConclusionBoth atmospheric PM2.5 and O3 can increase the risk of death from circulatory system diseases, and the two pollutants have a synergistic effect on the risk of death from circulatory system diseases.

In order to explore the distribution laws of air pollutants in different regions and at different times in the northern Anhui urban agglomeration and the relevant variables affecting the concentration of PM2.5 in the air, combined with the statistical data of Anhui Provincial Department of Ecology and Environment from 2018 to 2021 and relevant regional data, the principal component analysis ( PCA) method was used to analyze the correlation on the influencing factors of air quality by selecting monthly data and annual data respectively according to the time period and seasonal changes. The changes in the concentration of air pollutants PM2.5 and PM10 and other air pollutants in different seasons were compared and analyzed, and the backpropagation neural network (BP) based on PCA algorithm was constructed. A PCA-BP model was established and a cross-validation method was used to improve the accuracy of the model, and short-term prediction of PM2.5 concentration in the atmosphere is made. The experimental results show that the main influencing factors of PM2.5 concentration are PM10, CO, NO2 and SO2 . PM2.5 content in northern Anhui is higher in winter on the whole. The accuracy of the prediction model is higher in summer and autumn, but lower in winter. The prediction accuracy R2 of the four seasons reaches 0. 924, 0. 958, 0. 935 and 0. 794, respectively. [ABSTRACT FROM AUTHOR]

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ObjectiveTo explore the association between air pollutants and hospital outpatient visits in a district of Shanghai.MethodsDaily meteorological data， environmental data， data of outpatient visits to two secondary hospitals and two tertiary hospitals in this district from January 1， 2015 to December 31， 2019 were collected. A Poisson regression generalized linear model was used to analyze the exposure-response relationship between the air pollutants and hospital outpatient visits in this area.ResultsDuring the study period， the total number of outpatient visits in the included hospitals was 17 802 634， with an average daily total of （9 750±4 191） outpatient visits，and an average daily of （761±341） respiratory outpatient visits. In the lag effect of single pollutant model， when the concentration of air pollutant increased by 10 μg·m-3， PM2.5， SO2， NO2 had the maximum lag effect on the number of outpatient visits in the department of internal medicine for respiratory diseases on lag day 4， day 5 and day 7， respectively. And the RR values and 95%CI were 1.002 0（1.001 3‒1.002 6）， 1.0154（1.012 3‒1.018 5）， and 1.006 1（1.005 3‒1.006 9）， respectively.ConclusionThere is a exposure-response relationship between air pollutants and the number of outpatient visits in each department of the hospitals， and different pollutants have different degrees of lag effects.

Copyright of Asian Journals of Ecotoxicology is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Congenital heart disease (CHD) is the most common birth defect and one of the major causes of neonatal death, with an average prevalence of 9.4‰ worldwide. We reviewed recent epidemiological studies and found that exposure to air pollutants is associated with increased CHD risks, but the associations are inconsistent between exposure to air pollutants and different subtypes of CHD due to developmental and etiological heterogeneity among different subtypes of CHD. It has been reported that air pollutants are associated with increased risks of ventricular septal defect, patent ductus arteriosus, pulmonary stenosis, tetralogy of Fallot, and transposition of the great arteries. However, associations between maternal exposure to air pollutants and atrial septal defect (ASD) are contradictory, with significantly positive associations of inhalable particulate matter and nitrogen dioxide exposure, negative associations of fine particulate matter and carbon monoxide, and mixed associations of sulfur dioxide. Adverse effects of air pollutant on cardiac development cover a wide time window beyond 3-8 weeks during gestation; particulate matter and nitrogen oxide are more likely to affect fetal heart in early pregnancy, while the association strength of carbon monoxide shows a trough in early pregnancy, and sulfur dioxide and ozone affect cardiac health throughout pregnancy. In addition, we discussed the limitations of previous studies on the associations between maternal air pollutant exposure and CHD, and highlighted the application of precise assessment on exposure to air pollutants, the performance of prospective cohort studies and longitudinal studies, and the necessity of studies on CHD subtypes, in order to provide scientific evidence to control exposure to environmental pollutants and CHD occurrence.

BackgroundAir pollutants and extreme temperature both pose significant threats to human health, but the synergistic effect between air pollutants and temperature on health is inconsistent.ObjectiveTo explore a potential synergistic effect between air pollutants and temperature on the mortality in China through literature review.MethodsWanfang Data Knowledge Service Platform, China National Knowledge Infrastructure, VIP Information Chinese Journal Service Platform, PubMed, Web of Science, Science Direct, and Embase databases were searched. "Temperature" "air pollution" "mortality" were selected as keywords to collect literature on synergistic effect between air pollutants and temperature on mortality in China. Literature was published from 2000-01-01 to 2022-07-31 in Chinese or English. Two researchers screened the literature independently according to the inclusion criteria, and the results were integrated and analyzed after data extraction. The "meta" package of R software was used for meta-analysis.ResultsTwenty-seven studies met the inclusion criteria and associated air pollutants included PM10, PM2.5, O3, SO2, NO2, and CO. The impact of PM10 and PM2.5 on mortality in high temperature days was higher than that in moderate temperature days. In high temperature days, a 10 μg·m−3 increment in PM10 concentration corresponded to pooled estimates of 2.30% (95%CI: 1.34%-3.26%), 1.23% (95%CI: 0.64%-1.82%), and 1.42% (95%CI: 0.63%-2.22%) increase in non-accidental, cardiovascular, and respiratory mortalities, respectively. A 10 μg·m−3 increment in PM2.5 concentration corresponded to pooled estimates of 2.56% (95%CI: 2.00%-3.13%), 2.37% (95%CI: 1.64%-3.12%), and 2.14% (95%CI: 1.03%-3.25%) increase in non-accidental, cardiovascular, and respiratory mortalities, respectively. The synergistic effect of SO2 and NO2 on cardiovascular and respiratory mortalities in low temperature days was higher than that in moderate temperature days.ConclusionThe synergistic effects of air pollutants and temperature on mortality in low temperature days or in high temperature days are higher than that in moderate temperature days. The health protection related to these pollutants should be strengthened in these days.

Copyright of Chinese Journal of Contemporary Pediatrics is the property of Xiangya Medical Periodical Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

It is imperative to conduct collaborative planning for greenhouse gas and air pollutant control in China. At present, although the country has certain policies, laws, standards, institutions, and theoretical research as the basis for such planning, there are still deficiencies such as insufficient strategic coordination and a lack of effective connections of relevant plans, and the goals and requirements of collaborative control of greenhouse gases and air pollutants have not been fully incorporated into the territorial space planning, regional planning, and industrial development planning. In these circumstances, this study carries out text analysis and normative analysis and finds that the idea of improving the collaborative planning of greenhouse gas and air pollutant control mainly includes two aspects. The first is to strategically coordinate the collaborative control of greenhouse gases and air pollutants and determine its direction and long-term goal. Second, the collaborative control of greenhouse gases and air pollutants should be specifically deployed and arranged through the coordination of relevant plans. However, in order to fully realize the collaborative control of greenhouse gases and air pollutants by relevant plans, the following four aspects need to be guaranteed: ① We should further strengthen the coordination among the main bodies and strengthen unified supervision so as to provide the main body guarantee and supervision guarantee for the collaboration of related planners. ② We should strengthen theoretical research and further expand the scope of research to explore the relation⁃ ship between greenhouse gases (other than carbon dioxide) and air pollutants (including new pollutants). ③ We should formulate and re⁃ vise relevant policies, laws, and standards in a timely manner to assist collaborative planning. ④ We should actively carry out the pilot practice of collaborative control of greenhouse gases and air pollutants to explore the collaborative control mode that can be replicated and promoted and to accumulate practical experience for collaborative control planning. [ABSTRACT FROM AUTHOR]

Copyright of Refractories / Naihuo Cailiao is the property of Naihuo Cailia (Refractories) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Environmental Science & Technology (10036504) is the property of Editorial Board of Environmental Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Research of Environmental Sciences is the property of Research of Environmental Sciences Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study applied a de-weather method based on a machine learning technique to quantify the contribution of meteorology and emission changes to air quality from 2015 to 2021 in four cities in the Yangtze River Delta Region. The results showed that the significant reductions in PM 2.5 , NO 2 , and SO 2 emissions(57.2%-68.2%, 80.7%-94.6%, and 81.6%-96.1%, respectively) offset the adverse effects of meteorological conditions, resulting in lower pollutant concentrations. The meteorological contribution of maximum daily 8-h average O 3 (MDA8_O 3 ) showed a stronger effect than that of others(23.5%-42.1%), and meteorological factors promoted the increase in MDA8_O 3 concentrations(4.7%); however, emission changes overall resulted in a decrease in MDA8_O 3 concentrations(-3.2%). NO 2 and MDA8_O 3 decreased more rapidly from 2019 to 2021, mainly because the emissions played a stronger role in reducing pollutant concentrations than from 2015 to 2018. However, emissions changes had weaker reduction effects on PM 2.5 and SO 2 from 2019 to 2021 than from 2015 to 2018. De-weather methods could effectively seperate the effects of meteorology and emission changes on pollutant trends, which helps to evaluate the real effects of emission control policies on pollutant concentrations.

Given at the increasingly serious influence of air pollutants on the air environment in Xi’an; based on the ecological footprint theory, through the 2012—2016 Xi’an atmospheric pollutant discharge data, the ecological footprint and environmental carrying capacity of Xi’an air pollutants were quantitatively calculated and analyzed, revealing the trend of the ecological footprint characteristics of air pollutants in Xi’an in recent years. The results show that the ecological footprint of SO2 and NOx decreased in 2012—2016, and the rates of decline were 54.11% and 73.55%, respectively. The change of dust ecological footprint value was not obvious within 5 years. In recent years, the environmental carrying capacity of SO2, NOx and dust has increased. From 2012 to 2015, SO2 and NOx were ecological deficits in Xi’an,which showed a downward trend. In 2016, the SO2 ecological deficit rose to 8.995 4×108m2. In 2016, the SO2 pressure index was at the lowest level of 3, which was in an unsafe state. The ecological footprint of the ten-thousand-Yuan GDP of Xi’an SO2 and dust is higher than that of Beijing and Zhengzhou, while the value of NOx is the lowest. It is imperative for Xi’an to control industrial gas emissions, reduce the use of coal and form a green and efficient economic development model. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Fuzhou University is the property of Journal of Fuzhou University, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The random forest algorithm was used to separate the mass concentrations of six air pollutants (SO 2 , NO 2 , CO, PM 10 , PM 2.5 , and O 3 ) contributed by emissions and meteorological conditions. Their variations for five types of sites including Wuhan's central urban, suburb, industrial, the third ring road traffic, and urban background sites were investigated. The results showed that the values of PM 2.5 /CO, PM 10 /CO, and NO 2 /CO during the lockdown period decreased by 10.8-21.7, 9.34-24.7, and 14.4-22.1 times compared with the period before the lockdown, indicating that the contributions of emissions to PM 2.5 , PM 10 , and NO 2 were reduced. O 3 /CO increased by 50.1-61.5 times, implying that the secondary formation increased obviously. The contributions of emissions to various types of pollutants all increased after the lockdown. During the lockdown period, affected by the operation of some uninterrupted industrial processes, PM 2.5 concentrations in industrial areas dropped the least (20.5%). Compared with the lockdown period, residential activities, transportation, and industrial production were basically restored after the lockdown, resulting in the alleviation of the reduction in PM 2.5 emission-related concentrations. The increase in emission-related O 3 concentrations could be associated with the decreased NO and PM 2.5 concentrations during the lockdown period. The elevated O 3 partially offset the improved air quality brought by the reduced NO 2 and PM 2.5 concentrations. After the lockdown, ρ (O 3 ) related with meteorology at the suburban and urban background sites increased by 16.2 μg·m -3 and 16.1 μg·m -3 , respectively, which could be attributed to the increased ambient temperature and decreased relative humidity. The decrease in PM 2.5 and increase in O 3 concentrations caused by reduced traffic and industrial emissions at the third ring road traffic and central urban regions can provide reference for the current coordinated and precise control of PM 2.5 and O 3 in subregions.

Objectives: To investigate the epidemiological characteristics of respiratory Haemophilus influenzae (HI) infection in children in Suzhou, China and its association with climatic factors and air pollutants., Methods: The data on air pollutants and climatic factors in Suzhou from January 2016 to December 2019 were collected. Respiratory secretions were collected from 7 940 children with acute respiratory infection who were hospitalized during this period, and bacterial culture results were analyzed for the detection of HI. A stepwise regression analysis was used to investigate the association of HI detection rate with air pollutants (PM 2.5 , PM 10 , NO 2 , SO 2 , CO, and O 3 ) and climatic factors (monthly mean temperature, monthly mean humidity, monthly total rainfall, monthly total sunshine duration, and monthly mean wind speed)., Results: In 2016-2019, the 4-year overall detection rate of HI was 9.26% (735/7 940) among the children in Suzhou. The children aged <1 year and 1-<3 years had a significantly higher HI detection rate than those aged ≥3 years ( P <0.01). The detection rate of HI in spring was significantly higher than that in the other three seasons, and the detection rate of HI in autumn was significantly lower than that in the other three seasons ( P <0.001). The multiple linear regression analysis showed that PM 10 and monthly mean wind speed were independent risk factors for the detection rate of HI: the detection rate of HI was increased by 0.86% for every 10 µg/m 3 increase in the concentration of PM 10 and was increased by 5.64% for every 1 m/s increase in monthly mean wind speed. Air pollutants and climatic factors had a lag effect on the detection rate of HI., Conclusions: HI is an important pathogen for acute respiratory infection in children in Suzhou and is prevalent in spring. PM 10 and monthly mean wind speed are independent risk factors for the detection rate of HI.

Urban street canyon is one of the most important characteristics and spatial forms of cities. It is one of the most frequently used public spaces in cities, with the most serious automobile exhaust pollution and the largest population density. The unreasonable space configuration and internal composition might decrease self-purification of urban ventilation but increase local air pollutant concentration. Here, we reviewed the impacts of street canyon morphology, street trees, vehicle flow and meteorological factors on the distribution of air pollutants in street canyons. We scrutinized the relevant methods of numerical simulation, wind tunnel experiments, and field monitoring on the distribution and diffusion of air pollutants in street canyons. We recommended that future research should concentrate on the impacts of various parameters on the distribution and diffusion of air pollutants based on the field monitoring data. Meanwhile, further research should develop optimization strategies for street canyon design which is conducive to the dispersion of air pollutants, and put forward scientific support and optimization scheme for the controlling of air pollutants from the perspective of urban planning and pattern optimization.

Objective To explore the effect of air pollution on the number of emergency room visits for respiratory diseases in residents at different ages and its seasonal changes in Lanzhou,so as to provide a scientific basis for the early prevention of respiratory diseases in Lanzhou. Methods The daily number of emergency room visits for respiratory diseases in three class A hospitals in Lanzhou from January 1,2013 to December 31,2017,as well as the air pollutants and meteorological data of Lanzhou in the same period,was collected.After controlling the confounding factors including long-term trend of time,meteorological factors and day-of-week effect using a generalized additive model,we analyzed the relationships between air pollutants and the daily number of emergency room visits for respiratory diseases,and explored whether there was a lag effect of air pollutants.Results From 2013 to 2017,the emergency room visits for respiratory diseases in Lanzhou had a total number of 124 871,with an average of 69(1-367)visits per day.The single pollutant model showed that among the six conventional air pollutants monitored in Lanzhou,PM 2.5 ,PM 10 ,NO 2 ,SO 2 and O 3 8h had a lag effect on the number of emergency room visits for respiratory diseases.For every 10 μg/m 3 increase in the concentration of PM 2.5 (lag02: t =4.792, P =0.001), PM 10 (lag2: t =3.421, P <0.001), NO 2 (lag6: t =3.654, P =0.003), SO 2 (lag06: t =4.712, P <0.001)and O 3 8h (lag07: t =3.021, P =0.012), the number of emergency room visits for respiratory diseases increased by 0.900%(95% CI :0.573%-1.249%), 0.083%(95% CI :0.012%-0.153%), 1.293%(95% CI :0.867%-1.720%), 3.851%(95% CI :2.675%-5.041%)and 0.737%(95% CI :0.129%-1.348%), respectively.For every 1 mg/m 3 increase in the concentration of CO(lag0: t =3.564, P <0.001),the number of emergency room visits for respiratory diseases increased by 2.556% (95% CI : 1.493%-3.629%). In gender stratification, PM 2.5 (male: t =3.124, P =0.019;female: t =3.418, P =0.007), PM 10 (male: t =2.980, P =0.160;female: t =2.997, P =0.013)and CO(male: t =4.117, P =0.001;female: t =4.629, P <0.001)in winter had stronger effects on the emergency room visits for respiratory diseases in females than that in males, while the effects of NO 2 (male: t =3.020, P =0.107;female: t =3.006, P =0.128), SO 2 (male: t =4.101, P <0.001;female: t =3.820, P <0.001)and O 3 8h(male: t =3.660, P =0.022;female: t =3.517, P =0.018)in winter showed an opposite trend.In age stratification, the increase in the daily average concentration of PM 2.5 (0-14 years old: t =3.520, P =0.008), PM 10 (0-14 years old: t =3.840, P <0.001), SO 2 (0-14 years old: t =4.570, P <0.001), CO(0-14 years old: t =4.102, P =0.002)in winter would increase the emergency visits for respiratory diseases in the 0-14-year-old population.The daily average concentration of O 3 8h(0-14 years old: t =4.210, P <0.001;15-64 years old: t =3.807, P =0.001)in summer only affected the visits of the 0-14-year-old and the 15-64-year-old populations, and the air pollutants had no significant effect on the visits of those≥65 years old.The double pollutant model analysis revealed that after introducing 5 other pollutants respectively, PM 2.5 , PM 10 , NO 2 , SO 2 and O 3 8h significantly increased the emergency room visits for respiratory diseases, and CO had a more obvious effect than that predicted with the single pollutant model. Conclusion The rises in the concentrations of six air pollutants in Lanzhou will increase the emergency room visits for respiratory diseases, and the patterns vary with different genders, ages and seasons.

It is of great significance for joint prevention and control of air pollution to understand the spatial and temporal differentiation characteristics and regional driving factors of PM 2.5 in China. In this study, from a multi-scale perspective, the spatial pattern analysis and geographical detectors are used to explore the spatial and temporal distribution pattern and causes of PM 2.5 pollution in China mainland from 2011 to 2017. The results show that:① the annual average PM 2.5 concentration is relatively stable from 2011 to 2017, and there is no obvious trend. The change characteristics of regional PM 2.5 are similar to those of national PM 2.5 , showing a "W" shaped fluctuation. Overall, the order of pollution degree from high to low is:central, eastern, western, and northeastern. ② From the spatial pattern analysis results, we can see that the high-value cluster mainly appears in east China, middle China, and southwest of Xinjiang, while the low-value cluster appears in Qinghai-Tibet, Yunnan, Guizhou, Plateau, and Daxinganling regions. ③ The results of geographic detector analysis show that the population factor is the leading factor nationally; meanwhile, the industrial, energy consumption, and traffic factors all contribute to the distribution pattern of PM 2.5 in varying degrees. Regionally, besides the population factor, the proportion of secondary production and urban green space rate have the greatest impact on the northeast, the industrial smoke and dust and road area in the east, and the total industrial electricity and buses in the central area. The impact of social and economic factors does not significantly affect the PM 2.5 in the western region.

Based on anthropogenic source activity data and emission factors for the Sichuan Province, the 1 km×1 km-gridded atmospheric air pollutant emission inventory of 2015 was developed in combination with GIS technology and the combined "bottom-up" and "top-down" construction method. The results show that the total emission of SO 2 , NO x , CO, PM 10 , PM 2.5 , BC, OC, VOCs, and NH 3 in Chengdu is 444.9×10 3 , 820.0×10 3 , 3773.1×10 3 , 1371.6×10 3 , 537.5×10 3 , 28.7×10 3 , 53.1×10 3 , 923.6×10 3 , and 988.0×10 3 t, respectively. Power plants and other industrial combustion boilers contribute more than 95% of the SO 2 emissions. Mobile, fossil fuel combustion, and industrial process sources contribute 54%, 23%, and 20% of the NO x emissions, respectively. The industrial process of steel production and building materials manufacturing contribute 20% PM 10 of the emissions and take up 34% PM 2.5 of the emissions. Fugitive dust and road fugitive dust contributes 60% PM 10 and 35% PM 2.5 of the emissions, respectively. Biomass combustion contributes 33% BC and 51% OC of the emissions, respectively. The solvent use of mechanical processing, building decoration, electronic equipment manufacturing, and printing and furniture industry contribute 46% of the VOCs of the emissions. The NH 3 emissions mainly orginate from the sources of livestock feeding and nitrogen fertilizers, accounting for 70% and 25% of the NH 3 emissions, respectively. The spatial distribution of the emissions shows that high emissions are mainly distributed in the most densely populated, agricultural, and industrial more developed areas in Panzhihua and the Sichuan Basin. The urban agglomerations of the Chengdu Plain, represented by Chengdu, Deyang, and Mianyang, are the areas with emission concentration in the Sichuan Basin. The emissions inventory in this study has uncertainties. More fundamental studies on activity data should be conducted and the emission factors of typical emission sources should be further localized to improve the emission inventory and prevention and control of complex air pollution in the Sichuan Province and provide scientific support.