Air pollution characteristics and health risks in Henan Province, China

Long-term evolution of carbonaceous aerosols in PM2.5 during over a decade of atmospheric pollution outbreaks and control in polluted central China

Against the backdrop of an uncertain evolution of carbonaceous aerosols in polluted areas over the long term amid air pollution control measures, this 11-year study (2011-2021) investigated fine particulate matter (PM2.5) and carbonaceous components in polluted central China. Organic carbon (OC) and elemental carbon (EC) averaged 16.5 and 3.4 μg/m3, constituting 16 and 3 % of PM2.5 mass. Carbonaceous aerosols dominated PM2.5 (35 and 27 %) during periods of excellent and good air quality, while polluted days witnessed other components as dominants, with a significant decrease in primary organic aerosols and increased secondary pollution. From 2011 to 2021, OC and EC decreased by 53 and 76 %, displaying a high-value oscillation phase (2011-2015) and a low-value fluctuation phase (post-2016). A substantial reduction in high OC and EC concentrations in 2016 marked a milestone in significant air quality improvement attributed to effective control measures, especially targeting OC and EC, evident from their decreased proportion in PM2.5. Primary OC (POC) in winter exhibited the most pronounced reduction (8 % per year), and the seasonal disparities in PM2.5 and carbonaceous components were reduced, showcasing the effectiveness of control measures. Contrary to the more pronounced reduction of EC, which decreased in proportion to PM2.5, secondary OC (SOC) in PM2.5 exhibited an increasing trend. Along with rising OC/EC, SOC/OC, and SOC/EC ratios, this indicates a growing prominence of secondary pollution compared to the decrease in primary pollution. SOC shows an increasing trend with NO2 rise (r = 0.53), without O3 promoting SOC. Positive correlations of SOC with SO2, CO (r = 0.41, 0.59), also highlight their influence on atmospheric conditions, oxidative capacity, and chemical reactions, indirectly impacting SOC formation. The implementation of precise precursor emission reduction measures holds the key to future efforts in mitigating SOC pollution and reducing PM2.5 concentrations, thereby contributing to improved air quality.

Computational and experimental assessment of health risks of fine particulate matter in Nanjing and Yangzhou, China

Fine particulate matter (PM2.5) is a major air pollutant in most cities of China, and poses great health risks to local residents. In this study, the health effects of PM2.5 in Nanjing and Yangzhou were compared using computational and experimental methods. The global exposure mortality model (GEMM), including the results of a cohort study in China, was used to estimate the disease-related risks. Premature mortality attributable to PM2.5 exposure were markedly higher in Nanjing than that in Yangzhou at comparable levels of PM2.5 (8191 95% CI, 6975-9994 vs. 6548 95% CI, 5599-8049 in 2015). However, the baseline mortality rate was on a country-level and the age distribution was on a province-level, traditional estimation method could not accurately represent the health burdens of PM2.5 on a city-level. We proposed a refined calculation method which based on the actual deaths of each city and the disease death rates. Conversely, similar concentrations of PM2.5 exposure resulted in higher actual deaths per million population in Yangzhou (1466 95% CI, 1266-1746) than that in Nanjing (1271 95% CI, 1098-1514). Health risks of PM2.5 are associated with the generation of reactive oxygen species, among which hydroxyl radial (·OH) is the most reactive one. We then collected these PM2.5 samples and quantified the induced ·OH. Consistently, average ·OH concentration in 2015 was higher in Yangzhou than that in Nanjing, again indicating that PM2.5 in Yangzhou was more toxic. The combination of computational and experimental methods demonstrated the complex relationship between health risks and PM2.5 concentrations. The refined estimation method could help us better estimate and interpret the risks caused by PM2.5 exposure on a city-level.

Spatiotemporal characteristics of air pollutants and their associated health risks in '2+26' cities in China during 2016-2020 heating seasons

To understand characteristics of air pollutants and their associated health risks in recent heating seasons in China, ambient monitoring data of six air pollutants in '2 + 26' cities in Beijing-Tianjin-Hebei and its surrounding areas (known as the BTH2+26 cities) during 2016-2020 heating seasons was analyzed. Results show that daily average concentrations of PM2.5, PM10, SO2, NO2, and CO dropped significantly in BTH2+26 cities from the 2016-2017 heating season to 2019-2020 heating season, while 8h O3 increased markedly. During 2016-2020 heating seasons, annual average values of total excess risks (ERtotal) were 2.3% mainly contributed by PM2.5 (54.4%) and PM10 (36.1%). With PM2.5 pollution worsening, PM10 and NO2 were the important contribution factors of the enhanced ERtotal. Higher health-risk based air quality index (HAQI) values were mainly concentrated in the western Hebei and northern Henan. HAQI showed spatial agglomeration effect in four heating seasons. Impact factors of HAQI varied in different heating seasons. These findings can provide useful insights for China to further propose effective control strategies to alleviate air pollution in the future.

Comparison and implications of the carbonaceous fractions under different environments in polluted central plains in China: Insight from the lockdown of COVID-19 outbreak

Before and during the COVID-19 outbreak in the heated winter season of 2019, the carbonaceous fractions including organic carbon (OC), elemental carbon (EC), OC1-4, and EC1-5 were investigated between normal (November 1, 2019, to January 24, 2020) and lockdown (January 25, to February 29, 2020) periods in polluted regions of northern Henan Province. In comparison to urban site, four rural sites showed higher concentrations of carbonaceous components, especially secondary OC (SOC); the concentration of SOC in rural sites was 1.5-3.4 times that in the urban site. During the lockdown period, SOC in urban site decreased slightly, while it increased significantly in rural sites. NO₂ has a significant effect on SOC generation, particularly in normal period when NO₂ concentrations were high. Nevertheless, NO₂ significantly decreased, and the elevated O₃ (increased by 103-138%) contributed considerably to the generation of SOC during lockdown. Relative humidity (RH) promoted SOC production when RH was below 60%, but SOC was negatively correlated or uncorrelated with RH when RH exceeded 60%. Additionally, RH has a more pronounced effect on SOC during lockdown. The contribution of gasoline vehicle emissions decreases significantly in both urban and rural sites (3-12%) due to the significant reduction of anthropogenic activities during lockdown, although the urban site remained with the biggest contributions (37%). These results provide innovative insights into the variations in carbonaceous aerosols and SOC generation during the unique time when anthropogenic sources were significantly reduced and illustrate the differences in pollution characteristics and sources of carbonaceous fractions in different environments.

Effect of crude oil exploration and exploitation activities on soil, water and air in a Nigerian community

The continuous degradation of environmental ecosystems (land, water and soil) resulting from crude oil exploration and exploitation activities continues to gain global attention. This study investigates the effects of crude oil exploration and exploitation activities on soil, water and air in the study area. Soil samples were collected in three replicates at depths of 0-15 and 15-30 cm at sampling distances of 20, 100 and 200 m a from core oil exploitation operation area and a control point. Water samples were also taken from within the study area and analyzed using standard procedures. Major pollutants concentrations of particulate matter (PM_2.5 and PM₁₀) of the air were also measured using Air Quality Index (AQI). The results reveal that the soil, water and air parameters measured mostly at 20 m from the core oil operation area compromise the allowable standards provided for healthy living. In the same manner, some results at 100 and 200 m were slightly higher than the recommended values in some cases of heavy metals and bacteria activities in the soil. The AQI at 20 m was far above the permissible limit provided by the Environmental Protection Agency while others are gradually drawing towards the limit given for each pollutant. To safeguard the health of the residents of the host community and oil field workers, there is a need for proper and frequent environmental monitoring and assessment by authorized regulatory bodies in Nigeria. This will prevent any future exposure which may endanger the lives of the dwellers.

Air pollution and its associated health risks before and after COVID-19 in Shaanxi Province, China

Air pollution is a serious environmental problem that damages public health. In the present study, we used the segmentation function to improve the health risk-based air quality index (HAQI) and named it new HAQI (NHAQI). To investigate the spatiotemporal distribution characteristics of air pollutants and the associated health risks in Shaanxi Province before (Period I, 2015-2019) and after (Period II, 2020-2021) COVID-19. The six criteria pollutants were analyzed between January 1, 2015, and December 31, 2021, using the air quality index (AQI), aggregate AQI (AAQI), and NHAQI. The results showed that compared with AAQI and NHAQI, AQI underestimated the combined effects of multiple pollutants. The average concentrations of the six criteria pollutants were lower in Period II than in Period I due to reductions in anthropogenic emissions, with the concentrations of PM_2.5 (particulate matter ≤2.5 μm diameter), PM₁₀ (PM ≤ 10 μm diameter) SO₂, NO₂, O₃, and CO decreased by 23.5%, 22.5%, 45.7%, 17.6%, 2.9%, and 41.6%, respectively. In Period II, the excess risk and the number of air pollution-related deaths decreased considerably by 46.5% and 49%, respectively. The cumulative population distribution estimated using the NHAQI revealed that 61% of the total number of individuals in Shaanxi Province were exposed to unhealthy air during Period I, whereas this proportion decreased to 16% during Period II. Although overall air quality exhibited substantial improvements, the associated health risks in winter remained high.

Analysis of Factors Influencing Air Quality in Different Periods during COVID-19: A Case Study of Tangshan, China

This study aimed to analyze the main factors influencing air quality in Tangshan during COVID-19, covering three different periods: the COVID-19 period, the Level I response period, and the Spring Festival period. Comparative analysis and the difference-in-differences (DID) method were used to explore differences in air quality between different stages of the epidemic and different years. During the COVID-19 period, the air quality index (AQI) and the concentrations of six conventional air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃-8h) decreased significantly compared to 2017-2019. For the Level I response period, the reduction in AQI caused by COVID-19 control measures were 29.07%, 31.43%, and 20.04% in February, March, and April of 2020, respectively. During the Spring Festival, the concentrations of the six pollutants were significantly higher than those in 2019 and 2021, which may be related to heavy pollution events caused by unfavorable meteorological conditions and regional transport. As for the further improvement in air quality, it is necessary to take strict measures to prevent and control air pollution while paying attention to meteorological factors.

Characteristics, health risks, and premature mortality attributable to ambient air pollutants in four functional areas in Jining, China

Air pollution is one of the leading causes for global deaths and understanding pollutant emission sources is key to successful mitigation policies. Air quality data in the urban, suburban, industrial, and rural areas (UA, SA, IA, and RA) of Jining, Shandong Province in China, were collected to compare the characteristics and associated health risks. The average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, and CO show differences of -3.87, -16.67, -19.24, -15.74, and -8.37% between 2017 and 2018. On the contrary, O₃ concentrations increased by 4.50%. The four functional areas exhibited the same seasonal variations and diurnal patterns in air pollutants, with the highest exposure excess risks (ERs) resulting from O₃. More frequent ER days occurred within the 25-30°C, but much larger ERs are found within the 0-5°C temperature range, attributed to higher O₃ pollution in summer and more severe PM pollution in winter. The premature deaths attributable to six air pollutants can be calculated in 2017 and 2018, respectively. Investigations on the potential source show that the ER of O₃ (r of 0.86) had the tightest association with the total ER. The bivariate polar plots indicated that the highest health-based air quality index (HAQI) in IA influences the HAQI in UA and SA by pollution transport, and thus can be regarded as the major pollutant emission source in Jining. The above results indicate that urgent measures should be taken to reduce O₃ pollution taking into account the characteristics of the prevalent ozone formation regime, especially in IA in Jining.

The establishment of Air Quality Health Index in China: A comparative analysis of methodological approaches

BACKGROUND

The Air Quality Index (AQI) has been criticized because it does not adequately account for the health effect of multi-pollutants. Although the developed Air Quality Health Index (AQHI) is a more effective communication tool, little is known about the best method to construct AQHI on long time and large spatial scales.

OBJECTIVES

To further evaluate the validity of existing approaches to the establishment of AQHI on both long time and larger spatial scales.

METHODS

By introducing 3 approaches addressing multi-pollutant exposures: cumulative risk index (CRI), supervised principal component analysis (SPCA), and Bayesian multi-pollutants weighted model (BMP), we constructed CRI-AQHI, SPCA-AQHI, BMP-AQHI and standard-AQHI on cardiovascular mortality in China from 2015 to 2019 at both the national and geographic regional levels. We further assessed the performance of the four methods in estimating the joint effect of multi-pollutants by simulations under various scenarios of pollution effect.

RESULTS

The results of national China showed that the BMP-AQHI improved the goodness of fit of the standard-AQHI by 108.24%, followed by CRI-AQHI (5.02%), and all AQHIs performed better than AQI, consistent with 6 geographic regional results. In addition, the simulation result showed that the BMP method provided stable and relatively accurate estimations of the short-term combined effect of exposure to multi-pollutants.

CONCLUSIONS

AQHI based on BMP could communicate the air pollution risk to the public more effectively than the current AQHI and AQI.

Air Pollutants in Metropolises of Eastern Coastal China

Recently released hourly particular matter (PM:PM_2.5 and PM₁₀) and gaseous pollutants (SO₂, NO₂, CO, and O₃) data observed in Qingdao, Hangzhou, and Xiamen from 2015 to 2019 were utilized to reveal the current situation of air pollution over eastern coastal China. The PM pollution situation over the three metropolises ameliorated during studied period with the concentrations decreasing about 20-30%. Gas pollutants, excepting SO₂, generally exhibit no evident reduction tendencies, and a more rigorous control standard on gaseous pollutants is neededEven for the year 2018 with low pollution levels among the study period, these levels (<10% of PM_2.5, <6% of PM₁₀, and <15% of O₃) surpass the Grade II of the Chinese Ambient Air Quality Standard (CAAQS) over these metropolises of eastern coast China. No matter in which year, both SO₂ and CO concentrations are always below the Grade-II standards. According to the comparative analysis of PM_2.5/PM₁₀ and PM_2.5/CO during episode days and non-episode days, the formation of secondary aerosols associated with stagnant weather systems play an important role in the pollutant accumulation as haze episodes occurred. The stronger seasonal variations and higher magnitude occur in Qingdao and Hangzhou, while weaker seasonal variations and lower magnitudes occur in Xiamen. In Qingdao and Hangzhou, PM, NO₂, SO₂, and CO show relatively high levels in the cold wintertime and low levels in summer, whereas O₃ shows a completely opposite pattern. Xiamen exhibits high levels of all air pollutants except O₃ in spring due to its subtropical marine monsoon climate with mild winters. According to the back trajectory hierarchical clustering and concentration weighted trajectory (CWT) analysis, the regional transmission from adjacent cities has a significant impact on the atmospheric pollutant concentrations under the control of the prejudiced winds. Thus, besides local emission reduction, strengthening regional environmental cooperation and implementing joint prevention are effective measures to mitigate air pollution in the eastern coastal areas of China.

Spatial and temporal characteristics of air pollutants and their health effects in China during 2019-2020

This work presents the temporal and spatial characteristics of the major air pollutants and their associated health risks in China from 2019 to 2020, by using the monitoring data from 367 cities. The annual average PM_2.5, PM₁₀, NO₂, SO₂, CO, and O₃ concentrations decreased by 10.9%, 13.2%, 9.3%, 10.1%, 9.4%, and 5.5% from 2019 to 2020. National average PM_2.5 concentration in 2020 met the standard of 35 μg/m³, and that of O₃ decreased from 2019. COVID-19 lockdown affected NO₂ level dramatically, yet influences on PM_2.5 and O₃ were less clear-cut. Positive correlations between PM_2.5 and O₃ were found, even in winter in all five key regions, e.g., Jing-Jin-Ji (JJJ), FenWei Plain (FWP), Yangtze River Delta (YRD), Pearl River Delta (PRD) and Chengdu-Chongqing Region (CCR), indicating importance of secondary production for both PM_2.5 and O₃. Large seasonal variability of PM_2.5-SO₂ correlation indicates a varying role of SO₂ to PM_2.5 pollution in different seasons; and generally weak correlations in winter between PM_2.5 and NO₂ or SO₂ reveal the complexity of secondary formation processes to PM_2.5 pollution in winter. Multilinear regression analysis between PM_2.5 and SO₂, NO₂ and CO demonstrates that PM_2.5 is more sensitive to the change of NO₂ than SO₂ in JJJ, FWP, PRD and CCR, suggesting a priority of NO_x emission control for future PM_2.5 reduction. Furthermore, the new World Health Organization Air Quality Guidelines (WHO AQG2021) were adopted to calculate the excess health risks (ER) as well as the health-risk based air quality index (HAQI_WHO) of the pollutants. Such assessment points out the severity of air pollution associated health risks under strict standards: 40.0% of days had HAQI_WHO>100, while only 14.4% days had AQI>100. PM_2.5 ER was generally larger than O₃ ER, but O₃ ER in low PM_2.5 region (PRD) and during summer became more serious. Notably, NO₂ ER became even more important than PM_2.5 due to its strict limit of WHO AQG2021. Overall, our results highlight the increasing importance of O₃ in both air quality evaluation and health risk assessment, and the importance of coordinated mitigation of multiple pollutants (mainly PM_2.5, O₃ and NO₂) in protecting the public health.

Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China

The COVID-19 restrictions in 2020 have led to distinct variations in NO2 and O3 concentrations in China. Here, the different drivers of anthropogenic emission changes, including the effects of the Chinese New Year (CNY), China's 2018-2020 Clean Air Plan (CAP), and the COVID-19 lockdown and their impact on NO2 and O3 are isolated by using a combined model-measurement approach. In addition, the contribution of prevailing meteorological conditions to the concentration changes was evaluated by applying a machine-learning method. The resulting impact on the multi-pollutant Health-based Air Quality Index (HAQI) is quantified. The results show that the CNY reduces NO2 concentrations on average by 26.7% each year, while the COVID-lockdown measures have led to an additional 11.6% reduction in 2020, and the CAP over 2018-2020 to a reduction in NO2 by 15.7%. On the other hand, meteorological conditions from 23 January to March 7, 2020 led to increase in NO2 of 7.8%. Neglecting the CAP and meteorological drivers thus leads to an overestimate and underestimate of the effect of the COVID-lockdown on NO2 reductions, respectively. For O3 the opposite behavior is found, with changes of +23.3%, +21.0%, +4.9%, and -0.9% for CNY, COVID-lockdown, CAP, and meteorology effects, respectively. The total effects of these drivers show a drastic reduction in multi-air pollutant-related health risk across China, with meteorology affecting particularly the Northeast of China adversely. Importantly, the CAP's contribution highlights the effectiveness of the Chinese government's air-quality regulations on NO2 reduction.

Air pollutant spatiotemporal evolution characteristics and effects on human health in North China

North China, the political, economic, and cultural center of China, has been greatly harmed by frequent air pollution incidents. Therefore, it is vital to study air pollution characteristics and clarify their impact on human health. In this study, we first analyzed the spatiotemporal variations of air pollutants (PM_2.5, PM₁₀, CO, SO₂, NO₂, and O₃) in North China from 2016 to 2019. Then, the air quality index (AQI), aggregate air quality index (AAQI), and health risk based air quality index (HAQI) were used to assess health risks. Based on these, the AirQ_2.2.3 model was used to quantify health effects. The results showed that the major pollutant in the cities surrounding Beijing was PM_2.5, while PM₁₀ dominated in distant cities. Annual concentrations decreased (except for O₃), which is related to governmental emission reduction policies. However, O₃ concentrations increased owing to the complex precursor emissions. The AQI underestimated air pollution, while the AAQI and HAQI were accurate; the latter indicated that 55% of the study region population was exposed to polluted air. The AirQ_2.2.3 model quantified the total mortality proportions attributable to PM_2.5, PM₁₀, SO₂, CO, NO₂, and O₃, which were 1.87%, 3.12%, 1.11%, 1.40%, 4.19%, and 2.52%, respectively. In high concentrations, PM₁₀ and PM_2.5 pose significant health risks. The health effects of SO₂, NO₂, CO, and O₃ at lower concentrations were more obvious, indicating that the expected mortality rate due to low concentrations of some pollutants was much higher than that due to high concentrations of other pollutants.

Spatio-Temporal Characteristics of Air Quality Index (AQI) over Northwest China

In recent years, air pollution has become a serious threat, causing adverse health effects and millions of premature deaths in China. This study examines the spatial-temporal characteristics of ambient air quality in five provinces (Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX), and Qinghai (QH)) of northwest China (NWC) from January 2015 to December 2018. For this purpose, surface-level aerosol pollutants, including particulate matter (PMx, x = 2.5 and 10) and gaseous pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3)) were obtained from China National Environmental Monitoring Center (CNEMC). The results showed that fine particulate matter (PM2.5), coarse particulate matter (PM10), SO2, NO2, and CO decreased by 28.2%, 32.7%, 41.9%, 6.2%, and 27.3%, respectively, while O3 increased by 3.96% in NWC during 2018 as compared with 2015. The particulate matter (PM2.5 and PM10) levels exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II standards as well as the WHO recommended Air Quality Guidelines, while SO2 and NO2 complied with the CAAQS Grade II standards in NWC. In addition, the average air quality index (AQI), calculated from ground-based data, improved by 21.3%, the proportion of air quality Class I (0–50) improved by 114.1%, and the number of pollution days decreased by 61.8% in NWC. All the pollutants’ (except ozone) AQI and PM2.5/PM10 ratios showed the highest pollution levels in winter and lowest in summer. AQI was strongly positively correlated with PM2.5, PM10, SO2, NO2, and CO, while negatively correlated with O3. PM10 was the primary pollutant, followed by O3, PM2.5, NO2, CO, and SO2, with different spatial and temporal variations. The proportion of days with PM2.5, PM10, SO2, and CO as the primary pollutants decreased but increased for NO2 and O3. This study provides useful information and a valuable reference for future research on air quality in northwest China.

The Impact of Health and Wealth on Settlement Intention of Migrants: The Moderating Effect of Social Welfare

Background: With the rapid urbanization, citizenization of migrants is becoming the development tendency in China. It is significant to analyze the determining factors of the settlement intention of migrants.

Methods: The data we used were taken from the China Migrants Dynamic Survey (CMDS) in 2017. Multilevel mixed-effects logistic regression was used to analyze the relationship between air pollution, economic advantages, and settlement intention between different migrants and the moderating effect of social welfare.

Results: At the individual level, being female, married, urban and other ethnic, having higher education, older, and health associated with likelihood of settlement intention of migrants. Higher health education, social integration, and, have a health record were positively associated with the likelihood of settlement intention. Higher educated, urban areas, and Han migrants were willing to reduce their pursuit of health for economic development.

Conclusion: Health education and more social organizational participation can reduce the negative effect of air pollution and increase the positive effect of economic advantages on settlement intention of migrants. But, in less economically advantaged areas, it has no obvious effect. In the choice of health and wealth, the settlement intention of migrants shows difference, and unfairness and social welfare, in particular health education, can narrow this difference.

Prenatal exposure to air pollution and the risk of preterm birth in rural population of Henan Province

Due to the poor living and healthcare conditions, preterm birth (PTB) in rural population is a pressing health issue. However, PTB studies in rural population are rare. To explore the effects of air pollutants on PTB in rural population, we collected 697,316 medical records during 2014-2016 based on the National Free Preconception Health Examination Project. Logistic regression models were used to estimate the association between air pollutants and PTB and the modifying effects of demographic characteristics. Relative contribution and principal component analysis-generalized linear model (PCA-GLM) analysis were used to explore the most significant air pollutant and gestational period. Our results demonstrated that PTB risk is positively associated with exposure to air pollutants including PM₁₀, PM_2.5, SO₂, NO₂, and CO, while negatively associated with O₃ exposure (P < 0.05). In addition, we found that NO₂ was the largest contributor to the risk of PTB caused by air pollutants (26.5%). The third trimester of pregnancy was the most sensitive exposure window. PCA-GLM analysis showed that the first component (a combination of PM, SO₂, NO₂, and CO) increased the risk of PTB. Moreover, we found that rural women who are younger, had higher educated, multi-parity, or smoke appeared to be more sensitive to the association between air pollutants exposure and PTB (P_-interaction<0.05). Our findings suggested that increased air pollutants except O₃ were associated with elevated PTB risk, especially among vulnerable mothers. Therefore, the effects of air pollutants exposure on PTB should be mitigated by restricting emission sources of NO₂ and SO₂ in rural population, especially during the third trimester.

Air pollution increased risk of reproductive system diseases: a 5-year outcome analysis of different pollutants in different seasons, ages, and genders

Air pollution remains a serious environmental problem worldwide, and the effects of air pollutants with reproductive system diseases have already attracted extensive attention. The present study investigated the risk of air pollutants on reproductive system diseases, based on daily medical visits (DMV) of the past 5 years in central China. Data of DMV outpatients with reproductive system diseases were obtained from a general hospital in Zhengzhou, October 28, 2013 to May 31, 2018, as well as atmospheric pollutants data. Correlation of air pollutants and DMV was analyzed with distributed lag nonlinear model (DLNM), including total cases of reproductive system diseases, and in different seasons (spring, summer, autumn, and winter), genders (male and female), and age groups (<26, 26-35, and >35 years old). A total of 374,558 visits were included. NO2 was most closely relevant to incidence risk of total cases analysis with each increased interquartile ranges (IQRs) in the 6 pollutants, with 30-day lag. Relationship to pollutants was more sensitive in fall, >35 years old, and male groups than in other seasons, ages, and females, and NO2 had the highest risk on reproductive diseases. Air pollution increased risk of reproductive system diseases, and different pollutants played different roles in different seasons, ages, and genders. The results of this study will provide evidence for effective air quality controlling and human reproductive protection.

Relationship between Visibility, Air Pollution Index and Annual Mortality Rate in Association with the Occurrence of Rainfall—A Probabilistic Approach

An innovative method was proposed to facilitate the analyses of meteorological conditions and selected air pollution indices’ influence on visibility, air quality index and mortality. The constructed calculation algorithm is dedicated to simulating the visibility in a single episode, first of all. It was derived after applying logistic regression methodology. It should be stressed that eight visibility thresholds (Vis) were adopted in order to build proper classification models with a number of relevant advantages. At first, there exists the possibility to analyze the impact of independent variables on visibility with the consideration of its’ real variability. Secondly, through the application of the Monte Carlo method and the assumed classification algorithms, it was made possible to model the number of days during a precipitation and no-precipitation periods in a yearly cycle, on which the visibility ranged practically: Vis < 8; Vis = 8–12 km, Vis = 12–16 km, Vis = 16–20 km, Vis = 20–24 km, Vis = 24–28 km, Vis = 28–32 km, Vis > 32 km. The derived algorithm proved a particular role of precipitation and no-precipitation periods in shaping the air visibility phenomena. Higher visibility values and a lower number of days with increased visibility were found for the precipitation period contrary to no-precipitation one. The air quality index was lower for precipitation days, and moreover, strong, non-linear relationships were found between mortality and visibility, considering precipitation and seasonality effects.

Contrasting Iran's air quality improvement during COVID-19 with other global cities

BACKGROUND AND PURPOSE

In late 2019, a novel infectious disease (COVID-19) was identified in Wuhan China, which turned into a global pandemic. Countries all over the world have implemented some sort of lockdown to slow down its infection and mitigate it. This study investigated the impact of the COVID-19 pandemic on air quality during 1st January to 30th April 2020 compared to the same period in 2016-2019 in ten Iranian cities and four major cities in the world.

METHODS

In this study, the required data were collected from reliable sites. Then, using SPSS and Excel software, the data were analyzed in two intervals before and after the corona pandemic outbreak. The results are provided within tables and charts.

RESULTS

The current study showed the COVID-19 lockdown positively affected Iran's air quality. During the COVID-19 pandemic, the four-month mean air quality index (AQI) values in Tehran, Wuhan, Paris, and Rome were 76, 125, 55, and 60, respectively, which are 8 %, 22 %, 21 %, and 2 % lower than those during the corresponding period (83, 160, 70, and 61) from 2016 to 2019.

CONCLUSIONS

Although the outbreak of coronavirus has imposed devastating impacts on economy and health, it can have positive effects on air quality, according to the results.

Effect of Anti-COVID-19 Measures on Atmospheric Pollutants Correlated with the Economies of Medium-sized Cities in 10 Urban Areas of Grand Est Region, France

Using Sentinel-5P data, this study investigated the magnitude of change in the concentration of air pollutants (NO₂, HCHO, SO₂, O₃, CO, and aerosol index) in the air of ten cities and urban areas of the French region of Grand Est as a result of the first lockdown imposed between March 17, 2020 and May 11, 2020. The results showed that the air quality in the urban environments of Grand Est improved significantly compared to the same period in 2019 without lockdown. NO₂, O₃, aerosol index and CO were the pollutants that exhibited maximum reductions by an average of -33.98%, -5.94%, -26.82% and -0.66%, respectively (the observed maximum decreases were -54.7%, -7.7%, -13.1%, and -5.3%, respectively). The largest decrease occurred in the Public Establishments of Inter-municipal Cooperation (EPCI, in French: Établissement public de coopération intercommunale) areas of Eurométropole de Strasbourg, CA Colmar, and CA Mulhouse Alsace. The maximum decrease in air pollution first occurred in land cover classes close to cities, followed by built-up urban areas. In this study, a global depollution index known as the atmospheric clearance index (ACI) was developed, which involved several air pollution parameters, and quantitatively analyzed the decrease in contamination levels of the atmosphere in this region. In addition, the correlation between the novel ACI and other population and economic development indices was studied. The results indicated that there was a negative and statistically significant correlation between ACI and population density, gross domestic product, gross value added (GVA) at basic prices, number of employees, and active enterprises.

Does Industrial Air Pollution Increase Health Care Expenditure? Evidence From China

This paper discusses the impact of air pollution on medical expenditure in eastern, central, and western China by applying the fixed-effect model, random-effect model, and panel threshold regression model. According to theoretical and empirical analyses, there are different relationships between the two indexes in different regions of China. For eastern and central regions, it is obvious that the more serious the air pollution is, the more medical expenses there are. However, there is a non-linear single threshold effect between air pollution and health care expenditure in the western region. When air pollution is lower than this value, there is a negative correlation between them. Conversely, the health care expenditure increases with the aggravation of air pollution, but the added value is not enough to make up for the health problems caused by air pollution. The empirical results are basically consistent with the theoretical analysis, which can provide enlightenment for the government to consider the role of air pollution in medical expenditure. Policymakers should arrange the medical budget reasonably, according to its situation, to make up for the loss caused by air pollution.

Toxic metals in outdoor/indoor airborne PM2.5 in port city of Northern, China: Characteristics, sources, and personal exposure risk assessment

Outdoor and indoor PM_2.5 samples were simultaneously collected over four seasons (2017-2018) in Caofeidian, China, and analyzed for 15 elements to investigate the characteristics, sources, and health risks of PM_2.5-bound metals. Source-specific PM_2.5-bound metals were analyzed using positive matrix factorization, combined with the conditional probability function and potential source contribution function model. The health risks were evaluated using the health risk assessment model, which included the exposure parameters of indoor and outdoor activities of Chinese residents. The annual median of PM_2.5 concentrations (89.68 μg/m³) and total metals (2.67 μg/m³) from the outdoor samples significantly surpassed that of the indoor samples (51.56 μg/m³) and total metals (1.51 μg/m³) (P < 0.05). In addition, the indoor/outdoor concentration ratios indicated that most indoor metals mainly originated from outdoor emission sources. In the annual analysis of PM_2.5-bound metal sources, this study identified five metal sources: coal combustion, resuspended dust, traffic emissions, fuel combustion sources, and industrial sources, among which industry sources (36.6%) contributed the most. The non-carcinogenic risks of metals for adults (2.81) and children (2.80) all exceed the acceptable non-carcinogenic risk level (1). The non-carcinogenic risk of Mn (1.46 for children, 1.48 for adults) was a key factor in the total non-carcinogenic risk. The total carcinogenic risk of metals for children (3.75 × 10^-5) was above the acceptable level (1.0 × 10^-6) but within the tolerant limit (1.0 × 10^-4), and that for adults (1.48 × 10^-4) was above the tolerant limit. The lifetime carcinogenic risk of Cr⁶⁺ had the highest proportion of the total carcinogenic risk for children (87.5%) and adults (87.8%). Our results revealed that both adults and children suffered carcinogenic and non-carcinogenic risks from the PM_2.5-bound metals in Caofeidian. The corresponding emission control measures of metals in atmosphere should be considered.

Comparison of air pollutants and their health effects in two developed regions in China during the COVID-19 pandemic

Air pollution attributed to substantial anthropogenic emissions and significant secondary formation processes have been reported frequently in China, especially in Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD). In order to investigate the aerosol evolution processes before, in, and after the novel coronavirus (COVID-19) lockdown period of 2020, ambient monitoring data of six air pollutants were analyzed from Jan 1 to Apr 11 in both 2020 and 2019. Our results showed that the six ambient pollutants concentrations were much lower during the COVID-19 lockdown due to a great reduction of anthropogenic emissions. BTH suffered from air pollution more seriously in comparison of YRD, suggesting the differences in the industrial structures of these two regions. The significant difference between the normalized ratios of CO and NO2 during COVID-19 lockdown, along with the increasing PM2.5, indicated the oxidation of NO2 to form nitrate and the dominant contribution of secondary processes on PM2.5. In addition, the most health risk factor was PM2.5 and health-risked based air quality index (HAQI) values during the COVID-19 pandemic in YRD in 2020 were all lower than those in 2019. Our findings suggest that the reduction of anthropogenic emissions is essential to mitigate PM2.5 pollution, while O3 control may be more complicated.

Spatial and Temporal Characteristics of Environmental Air Quality and Its Relationship with Seasonal Climatic Conditions in Eastern China during 2015-2018

Exploring the relationship between environmental air quality (EAQ) and climatic conditions on a large scale can help better understand the main distribution characteristics and the mechanisms of EAQ in China, which is significant for the implementation of policies of joint prevention and control of regional air pollution. In this study, we used the concentrations of six conventional air pollutants, i.e., carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), fine particulate matter (PM_2.5), coarse particulate matter (PM₁₀), and ozone (O₃), derived from about 1300 monitoring sites in eastern China (EC) from January 2015 to December 2018. Exploiting the grading concentration limit (GB3095-2012) of various pollutants in China, we also calculated the monthly average air quality index (AQI) in EC. The results show that, generally, the EAQ has improved in all seasons in EC from 2015 to 2018. In particular, the concentrations of conventional air pollutants, such as CO, SO₂, and NO₂, have been decreasing year by year. However, the concentrations of particulate matter, such as PM_2.5 and PM₁₀, have changed little, and the O₃ concentration increased from 2015 to 2018. Empirical mode decomposition (EOF) was used to analyze the major patterns of AQI in EC. The first mode (EOF1) was characterized by a uniform structure in AQI over EC. These phenomena are due to the precipitation variability associated with the East Asian summer monsoon (EASM), referred to as the "summer-winter" pattern. The second EOF mode (EOF2) showed that the AQI over EC is a north-south dipole pattern, which is bound by the Qinling Mountains and Huaihe River (about 35° N). The EOF2 is mainly caused by seasonal variations of the mixed concentration of PM_2.5 and O₃. Associated with EOF2, the Mongolia-Siberian High influences the AQI variation over northern EC by dominating the low-level winds (10 m and 850 hPa) in autumn and winter, and precipitation affects the AQI variation over southern EC in spring and summer.

Characteristics and sources of atmospheric pollutants in typical inland cities in arid regions of central Asia: A case study of Urumqi city

The arid zone of central Asia secluded inland and has the typical features of the atmosphere. Human activities have had a significant impact on the air quality in this region. Urumqi is a key city in the core area of the Silk Road and an important economic center in Northwestern China. The urban environment is playing an increasingly important role in regional development. To study the characteristics and influencing factors of the main atmospheric pollutants in Urumqi, this study selected Urumqi's daily air quality index (AQI) data and observation data of six major pollutants including fine particulate matter (PM2.5), breathable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3_8h) from 2014 to 2018 in conjunction with meteorological data to use a backward trajectory analysis method to study the main characteristics of atmospheric pollutants and their sources in Urumqi from 2014 to 2018. The results showed that: (1) From 2014 to 2018, the annual average of PM2.5, PM10, SO2, NO2 and CO concentrations showed a downward trend, and O3_8h concentrations first increased, then decreased, and then increased, reaching the highest value in 2018 (82.15 μg·m-3); The seasonal changes of PM2.5, PM10, SO2, NO2 and CO concentrations were characterized by low values in summer and fall seasons and high values in winter and spring seasons. The concentration of O3_8h, however, was in the opposite trend, showing the high values in summer and fall seasons, and low values in winter and spring seasons. From 2014 to 2018, with the exception of O3_8h, the concentration changes of the other five major air pollutants were high in December, January, and February, and low in May, June, and July; the daily changes showed a "U-shaped" change during the year. The high-value areas of the "U-shaped" mode formed around the 50th day and the 350th day. (2) The high-value area of AQI was from the end of fall (November) to the beginning of the following spring (March), and the low-value area was from April to October. It showed a U-shaped change trend during the year and the value was mainly distributed between 50 and 100. (3) The concentrations of major air pollutants in Urumqi were significantly negatively correlated with precipitation, temperature, and humidity (P<0.01), and had the highest correlation coefficients with temperature. (4) Based on the above analysis results, this study analyzed two severe pollution events from late November to early December. Analysis showed that the PM2.5/PM10 ratio in two events remained at about 0.1 when the pollution occurred, but was higher before and after the pollution (up to 1.46). It was shown that the pollution was a simple sandstorm process. Backward trajectory analysis clustered the airflow trajectories reaching Urumqi into 4 categories, and the trajectories from central Asia contributed the maximum values of average PM2.5 and PM10 concentrations.

Impact of atmospheric pollution on asthma and bronchitis based on lichen biomonitoring using IAP, IHI and GIS in Algiers Bay (Algeria)

We investigated the association between air pollution and asthma and bronchitis hospital admissions in Algiers city (Algeria). In addition, we used geographic information systems (GIS) and statistical methods to evaluate their correlation with the atmospheric pollution estimated by the lichen biomonitoring method of the index of atmospheric purity (IAP), the index of human impact (IHI) and environmental parameters. Thus, we georeferenced 976 local patients (including 771 patients with asthma and 205 patients with bronchitis). Then, we compared the patients to the spatial distribution of IAP in thirty-five areas (communities). The results revealed a significant difference in the mean spatial variation in the diseases among those areas. In fact, maps and generalized linear models (GLMs) revealed a significant negative correlation between IAP and diseases. Therefore, redundancy analysis (RDA) and Monte Carlo tests described a significant effect of IAP, urbanization and the number of roads on the distribution of diseases. We hope our findings contribute to enriching the literature on health research with a low-cost method of monitoring outdoor air pollution.

Disentangling the contributions of urban and production sources in short- and medium-chain chlorinated paraffin concentrations in a complex source region

Short-chain chlorinated paraffins (SCCPs) and medium-chain chlorinated paraffins (MCCPs) were measured in tree bark samples. These samples were collected around a chemical industrial park containing several chlorinated paraffin (CP) production plants, in a nearby city (Zhengzhou), and along a transect between the industrial park and city. Theoretical air concentrations were back-calculated from concentrations in bark using a predictive equation for estimating equilibrium bark-air partition coefficients. We developed this equation from a series of previously published K_bark-air measurements. Comparison of the normalized concentration profiles along south to north transects showed that wind played only a minor role in CP concentrations and profiles in the region. Three distinct source profiles were found in the complex source region. A fingerprint analysis technique was used to quantify the contribution of each source to the CP burden at various locations along the transect. We found that CP profiles at sites up to 6 km from the industrial park were strongly influenced by CP plant emissions, whereas the sites located in the rural zone and rural-urban interface were influenced by a mixture of CP plant emissions and the neighboring city.

Temporal variations and spatial distributions of gaseous and particulate air pollutants and their health risks during 2015-2019 in China

Air quality has been significantly improved in China in recent years; however, our knowledge of the long-term changes in health risks from exposure to air pollutants remain less understood. Here we investigated the temporal variations and spatial distributions of six criteria pollutants (SO₂, NO₂, O₃, CO, PM_2.5 and PM₁₀) in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) during 2015-2019. SO₂ showed 36-60% reductions in three regions, comparatively, NO₂ decreased by 3-17% in BTH and YRD and had a 5% increase in PRD. PM_2.5 and PM₁₀ showed the largest reductions in BTH (30-33%) and the lowest in PRD (7-13%), while O₃ increased by 9% during 2015-2019 particularly in BTH and YRD. Assuming that only air pollutants above given thresholds exert excess risk (ER_total) of mortality, we found that the different variations of pollutants have caused ER_total in BTH decreasing significantly from 4.8% in 2015 to 2.0% in 2019, while from 1.9% to 1.0% in YRD, and a small change in PRD. These results indicate substantially decreased health risks of mortality from exposure to air pollutants as a response to improved air quality. Overall, PM_2.5 dominated ER_total accounting for 42-53% in BTH and 58-64% in YRD with steadily increased contributions, yet ER_total presented strong seasonal dependence on air pollutants with largely increased contribution of O₃ in summer. The ER_total caused by SO₂ was decreased substantially and became negligible except in winter in BTH, while NO₂ only played a role in winter. We also found that ER_PM2.5 was compositional dependent with organics being the major contributor at low ER_PM2.5 while nitrate was more important at high ER_PM2.5. Our results highlight that evaluation of public health risks of air pollution needs to consider chemical differences of PM in different regions in addition to dominant air pollutants in different seasons.

Temporal and spatial discrepancies of VOCs in an industrial-dominant city in China during summertime

Ozone (O₃) pollution is currently problematic to cities across the globe. Many non-methane hydrocarbons (NMHCs) are efficient O₃ precursors. In this study, target volatile organic compounds (VOCs), including oxygenated VOCs (known as carbonyls), were monitored at eight sampling sites distributed in urban and suburban in the typical and industrial-dominant city of Shaoxing, Zhejiang province, China. At the suburban sites, C₈-C₁₂ alkanes, aromatics with lower reactivity (k_OH <13 × 10^-12 cm³ mol^-1 s^-1) and acetonitrile were more abundant than urban ones due to higher emissions from diesel-fueled trucks and biomass burning. In general, higher abundances of total quantified NMHCs (ΣNMHC) were found on high O₃ (HO) days. The increments of formaldehyde (C₁) and O₃ were higher in urban than suburban, while a reverse trend was seen for acetaldehyde (C₂). Substantial and local biogenic inputs of C₂ were found in suburban in the afternoon when both temperature and light intensity reached maximum of the day. In urban, higher increment was found for O₃ than the carbonyls, representing that the secondary formation of O₃ was more efficient. Distance decay gradient of most representative NMHCs were positively correlated to the distances from a westernmost industrial origin located at the upwind location. The net loss rates of the NMHCs ranged from -0.009 to -0.11 ppbv km^-1, while the higher rates were seen for the most reactive species like C₂-C₄ alkenes. The results and interpretation of this study are informative to establish efficient local control measures for O₃ and the related percussors for the microscale industrial cities in China.

Changes of air quality and its associated health and economic burden in 31 provincial capital cities in China during COVID-19 pandemic

With outbreak of the novel coronavirus disease (COVID-19), immediate prevention and control actions were imposed in China. Here, we conducted a timely investigation on the changes of air quality, associated health burden and economic loss during the COVID-19 pandemic (January 1 to May 2, 2020). We found an overall improvement of air quality by analyzing data from 31 provincial cities, due to varying degrees of NO2, PM2.5, PM10 and CO reductions outweighing the significant O3 increase. Such improvement corresponds to a total avoided premature mortality of 9410 (7273-11,144) in the 31 cities by comparing the health burdens between 2019 and 2020. NO2 reduction was the largest contributor (55%) to this health benefit, far exceeding PM2.5 (10.9%) and PM10 (23.9%). O3 instead was the only negative factor among six pollutants. The period with the largest daily avoided deaths was rather not the period with strict lockdown but that during February 25 to March 31, due to largest reduction of NO2 and smallest increase of O3. Southwest, Central and East China were regions with relatively high daily avoided deaths, while for some cities in Northeast China, the air pollution was even worse, therefore could cause more deaths than 2019. Correspondingly, the avoided health economic loss attributable to air quality improvement was 19.4 (15.0-23.0) billion. Its distribution was generally similar to results of health burden, except that due to regional differences in willingness to pay to reduce risks of premature deaths, East China became the region with largest daily avoided economic loss. Our results here quantitatively assess the effects of short-term control measures on changes of air quality as well as its associated health and economic burden, and such information is beneficial to future air pollution control.

Air pollution characteristics, health risks, and source analysis in Shanxi Province, China

China is confronting an unprecedented air pollution problem. This study discussed the characteristics of air pollution and its risks on human health and conducted source analysis combined with local development in Shanxi Province in 2016 and 2017. Results demonstrated that the air pollution situation in Shanxi was deteriorating, with Taiyuan, Yangquan, Changzhi, Jincheng, Jinzhong, and Linfen being heavily polluted districts. Particulate matter (PM) was considered the major pollutant, but nitrogen dioxide and ozone showed a dominant trend recently. Furthermore, the health risks evaluated on the basis of a comprehensive air quality index (AAQI) and an aggregated risk index revealed a relatively high-risk level in Shanxi. Among the pollutants, the largest contributor was PM, followed by sulfur dioxide and ozone. Southern Shanxi had the largest pollution level and health risks, whereas Datong was the least polluted region. Source analysis suggested that the main driving forces of air pollution, besides natural factors, were urbanization, population size, civil vehicles, coal-based heavy industries, and high-energy consumption. Therefore, strengthening urban greening, vigorously adjusting and optimizing the industrial structure, and formulating a multi-domain cooperative control regime on air pollution, especially PM and ozone, should be promoted.

Air Pollution Characteristics and Health Risks in the Yangtze River Economic Belt, China during Winter

The air pollution characteristics of six ambient criteria pollutants, including particulate matter (PM) and trace gases, in 29 typical cities across the Yangtze River Economic Belt (YREB) from December 2017 to February 2018 are analyzed. The overall average mass concentrations of PM_2.5, PM₁₀, SO₂, CO, NO₂, and O₃ are 73, 104, 16, 1100, 47, and 62 µg/m³, respectively. PM_2.5, PM₁₀, and NO₂ are the dominant major pollutants to poor air quality, with nearly 83%, 86%, and 59%, exceeding the Chinese Ambient Air Quality Standard Grade I. The situation of PM pollution in the middle and lower reaches is more serious than that in the upper reaches, and the north bank is more severe than the south bank of the Yangtze River. Strong positive spatial correlations for PM concentrations between city pairs within 300 km is frequently observed. NO₂ pollution is primarily concentrated in the Suzhou-Wuxi-Changzhou urban agglomeration and surrounding areas. The health risks are assessed by the comparison of the classification of air pollution levels with three approaches: air quality index (AQI), aggregate AQI (AAQI), and health risk-based AQI (HAQI). When the AQI values escalate, the air pollution classifications based on the AAQI and HAQI values become more serious. The HAQI approach can better report the comprehensive health effects from multipollutant air pollution. The population-weighted HAQI data in the winter exhibit that 50%, 70%, and 80% of the population in the upstream, midstream, and downstream of the YREB are exposed to polluted air (HAQI > 100). The current air pollution status in YREB needs more effective efforts to improve the air quality.

Effects of China's current Air Pollution Prevention and Control Action Plan on air pollution patterns, health risks and mortalities in Beijing 2014-2018

Beijing is one of the most polluted cities in the world. However, the "Air Pollution Prevention and Control Action Plan" (APPCAP), introduced since 2013 in China, has created an unprecedented drop in pollution concentrations for five major pollutants, except O₃, with a significant drop in mortalities across most parts of the city. To assess the effects of APPCAP, air pollution data were collected from 35 sites (divided into four types, namely, urban, suburban, regional background, and traffic) in Beijing, from 2014 to 2018 and analyzed. Simultaneously, health-risk based air quality index (HAQI) and district-specific pollution (PM_2.5 and O₃) attributed mortality were calculated for Beijing. The results show that the annual PM_2.5 concentration exceeded the Chinese national ambient air quality standard Grade II (35 μg/m³) in all sites, ranging from 88.5 ± 77.4 μg/m³ for the suburban site to 98.6 ± 89.0 μg/m³ for the traffic site in 2014, but was reduced to 50.6 ± 46.6 μg/m³ for the suburban site, and 56.1 ± 47.0 μg/m³ for the regional background in 2018. O₃ was another most important pollutant that exceeded the Grade II standard (160 μg/m³) for a total of 291 days. It peaked at 311.6 μg/m³ in 2014 for the urban site and 290.6 μg/m³ in 2018 in the suburban site. APPCAP led to a significant reduction in PM_2.5, PM₁₀, NO₂, SO₂ and CO concentrations by 7.4, 8.1, 2.4, 1.9 and 80 μg/m³/year respectively, though O₃ concentration was increased by 1.3 μg/m³/year during the five-years. HAQI results suggest that during the high pollution days, the more vulnerable groups, such as the children, and the elderly, should take additional precautions, beyond the recommendations currently put forward by Beijing Municipal Environmental Monitoring Center (BJMEMC). In 2014, PM_2.5 and O₃ attributed to 29,270 and 3,030 deaths respectively, though in 2018 their mortalities were reduced by 5.6% and 18.5% respectively. The highest mortality was observed in Haidian and Chaoyang districts, two of the most densely populated areas in Beijing. Beijing's air quality has seen a dramatic improvement over the five-year period, which can be attributable to the implementation of APPCAP and the central government's determination, with significant drops in the mortalities due to PM_2.5 and O₃ in parallel. To further improve air quality in Beijing, more stringent regulatory measures should be introduced to control volatile organic compounds (VOCs) and reduce O₃ concentrations. Consistent air pollution control interventions will be needed to ensure long-term prosperity and environmental sustainability in Beijing, China's most powerful city. This study provides a robust methodology for analyzing air pollution trends, health risks and mortalities in China. The crucial evidence generated forms the basis for the governments in China to introduce location-specific air pollution policy interventions to further reduce air pollution in Beijing and other parts of China. The methodology presented in this study can form the basis for future fine-grained air pollution and health risk study at the city-district level in China.

Insight into monsoon for shaping the air quality of Islamabad, Pakistan: Comparing the magnitude of health risk associated with PM10 and PM2.5 exposure

Monsoon plays a determinant role in defining the air quality of many Asian countries. Filter-based 24 h ambient PM₁₀ and PM_2.5 sampling was performed by using two paralleled medium volume air samplers during pre-and post-monsoon periods. A negligible change in PM_2.5 mass concentration from 45.77 to 44.46 µg/m³ compared to PM₁₀ from 74.34 to 142.49 µg/m³ was observed after the monsoon season. The air quality index (AQI) results showed that the air quality of the city retained from good to slightly polluted in both periods, where PM_2.5 remained as the main detrimental to air quality in 95% of the total days. The NOAA HYSPLIT model analysis and wind rose patterns showed air trajectories, especially in post-monsoon originated from relatively polluted areas transported higher PM₁₀. Meteorological attributes indicated a more conducive atmospheric condition for secondary pollution in the pre-monsoon. Evidence showed post-monsoon as a more polluted period, compared to the pre-monsoon and would pose an extra 1.07 × 10^-3 lifetime risk to the local population. Similarly, a higher level of PM₁₀ in the post-monsoon caused 43% more premature mortality and 41% more deaths from all-cause mortality compare to the pre-monsoon period, respectively. Implications: Pakistan is an under-developing country where pollution monitoring studies are decidedly limited. Notably, studies, concise PM_2.5 and health assessment are deficient. The present study may contribute to evaluating the air quality in special events such as monsoon and can also provide scientific and technical support for subsequent air pollution research. Moreover, the results help to develop adequate prevention and pollution control strategies and offer policy suggestions for monsoon observing countries in general and in particular, in Islamabad, Pakistan. These findings provide essential arguments in favor of educating people and raising awareness about the detrimental health effects of air pollution. Improving the quality of life of people with cardiovascular and respiratory disorders requires an immediate and substantial reduction of air pollution.

Bacterial composition and community structure of the oropharynx of adults with asthma are associated with environmental factors

The development and exacerbation of asthma are mainly attributed to inflammatory reactions caused by allergens. However, less is known about the development of asthma caused by microbial disorders in the oropharynx and induced by environmental factors. Here, the metagenome of the oropharyngeal microbiome of adults with asthma was analysed to identify their association with air pollutants. Oropharyngeal swabs from patients with asthma were collected in two winters (W1 and W2) with different environmental factor exposures. The bacterial composition and community structure of the oropharynx were analysed through high-throughput sequencing. After analysis, the α-diversity and β-diversity exhibited significant differences between the two groups. LEfSe analysis detected 8 significantly different phyla and 11 significantly different genera between the W1 and W2 groups. Multiple linear regression analyses found that the asthma status might contribute to the alteration of microbial composition. Redundancy analysis showed that NO₂ was the only environmental factor that significantly affected the microbial community structure of the oropharynx. The different genera associated with NO₂ were Rothia, Actinomyces, Fusobacterium and Leptotrichia. The altered taxa related to PM_2.5 were Cupriavidus and Acinetobacter. Actinobacillus and Prevotella showed a highly positive correlation with O₃. Moreover, network analysis was carried out to explore the co-occurrence relationships of the main genera, and PICRUSt was conducted to predict bacterial functions. This study showed that environmental factors might cause alteration in the oropharyngeal flora, which might be a potential risk factor of asthma.

Pollution Weather Prediction System: Smart Outdoor Pollution Monitoring and Prediction for Healthy Breathing and Living

Air pollution has been a looming issue of the 21st century that has also significantly impacted the surrounding environment and societal health. Recently, previous studies have conducted extensive research on air pollution and air quality monitoring. Despite this, the fields of air pollution and air quality monitoring remain plagued with unsolved problems. In this study, the Pollution Weather Prediction System (PWP) is proposed to perform air pollution prediction for outdoor sites for various pollution parameters. In the presented research work, we introduced a PWP system configured with pollution-sensing units, such as SDS021, MQ07-CO, NO2-B43F, and Aeroqual Ozone (O₃). These sensing units were utilized to collect and measure various pollutant levels, such as PM2.5, PM10, CO, NO₂, and O₃, for 90 days at Symbiosis International University, Pune, Maharashtra, India. The data collection was carried out between the duration of December 2019 to February 2020 during the winter. The investigation results validate the success of the presented PWP system. In the conducted experiments, linear regression and artificial neural network (ANN)-based AQI (air quality index) predictions were performed. Furthermore, the presented study also found that the customized linear regression methodology outperformed other machine-learning methods, such as linear, ridge, Lasso, Bayes, Huber, Lars, Lasso-lars, stochastic gradient descent (SGD), and ElasticNet regression methodologies, and the customized ANN regression methodology used in the conducted experiments. The overall AQI values of the air pollutants were calculated based on the summation of the AQI values of all the presented air pollutants. In the end, the web and mobile interfaces were developed to display air pollution prediction values of a variety of air pollutants.

Dynamic linkages among economic development, environmental pollution and human health in Chinese

Background

Research on the relationships between economic development, energy consumption, environmental pollution, and human health has tended to focus on the relationships between economic growth and air pollution, energy and air pollution, or the impact of air pollution on human health. However, there has been little past research focused on all the above associations.

Methods

The few studies that have examined the interconnections between the economy, energy consumption, environmental pollution and health have tended to employ regression analyses, DEA (Data Envelopment Analysis), or DEA efficiency analyses; however, as these are static analysis tools, the analyses did not fully reveal the sustainable economic, energy, environmental or health developments over time, did not consider the regional differences, and most often ignored community health factors. To go some way to filling this gap, this paper developed a modified two stage Undesirable Meta Dynamic Network model to jointly analyze energy consumption, economic growth, air pollution and health treatment data in 31 Chinese high-income and upper-middle income cities from 2013-2016, for which the overall efficiency, production efficiency, healthcare resource utilization efficiency and technology gap ratio (TGR) for all input and output variables were calculated.

Results

It was found that: (1) the annual average overall efficiency in China's eastern region was the highest; (2) the production stage efficiencies were higher than the healthcare resource utilization stage efficiencies in most cities; (3) the high-income cities had lower TGRs than the upper-middle income cities; (4) the high-income cities had higher average energy consumption efficiencies than the upper-middle income cities; (5) the health expenditure efficiencies were the lowest of all inputs; (6) the high-income cities' respiratory disease and mortality rate efficiencies were higher than in the upper-middle income cities, which had improving mortality rate efficiencies; and (7) there were significant regional differences in the annual average input and output indicator efficiencies.

Conclusions

First, the high-income cities had higher average efficiencies than the upper-middle income cities. Of the ten eastern region high-income cities, Guangzhou and Shanghai had average efficiencies of 1, with the least efficient being Shijiazhuang. In the other regions, the upper-middle income cities required greater technology and health treatment investments. Second, Guangzhou, Lhasa, Nanning, and Shanghai had production efficiencies of 1, and Guangzhou, Lhasa, Nanning, Shanghai and Fuzhou had healthcare resource utilization efficiencies of 1. As the average production stage efficiencies in most cities were higher than the healthcare resource utilization stage efficiencies, greater efforts are needed to improve the healthcare resource utilization. Third, the technology gap ratios (TGRs) in the high-income cities were slightly higher than in the upper-middle income cities. Therefore, the upper-middle income cities need to learn from the high-income cities to improve their general health treatment TGRs. Fourth, while the high-income cities had higher energy consumption efficiencies than the upper-middle income cities, these were decreasing in most cities. There were few respiratory disease efficiency differences between the high-income and upper-middle income cities, the high-income cities had falling mortality rate efficiencies, and the upper-middle income cities had increasing mortality rate efficiencies. Overall, therefore, most cities needed to strengthen their health governance to balance economic growth and urban expansion. Fifth, the average AQI efficiencies in both the high-income and upper-middle income cities were higher than the average CO₂ efficiencies. However, the high-income cities had lower average CO₂ emissions and AQI efficiencies than the upper-middle income cities, with the AQI efficiency differences between the two city groups expanding. As most cities were focusing more on air pollution controls than carbon dioxide emissions, greater efforts were needed in coordinating the air pollution and carbon dioxide emissions treatments. Therefore, the following suggestions are given. (1) The government should reform the hospital and medical systems. (2) Local governments need to strengthen their air pollution and disease education. (3) High-income cities need to improve their healthcare governance to reduce the incidence of respiratory diseases and the associated mortality. (4) Healthcare governance efficiency needs to be prioritized in 17 upper-middle income cities, such as Hangzhou, Changchun, Harbin, Chengdu, Guiyang, Kunming and Xi'an, by establishing sound medical management systems and emergency environmental pollution treatments, and by increasing capital asset medical investments. (5) Upper-middle income cities need to adapt their treatment controls to local conditions and design medium to long-term development strategies. (6) Upper-middle income cities need to actively learn from the technological and governance experiences in the more efficient higher-income cities.

Air pollution characteristics and human health risks in key cities of northwest China

Air pollution events occur frequently in northwest China, which results in serious detrimental effects on human health. Therefore, it is essential to understand the air pollution characteristics and assess the risks to humans. In this study, we analyzed the pollution characteristics of criteria pollutants in six key cities in northwest China from 2015 to 2018. We used the air quality index (AQI), aggregate AQI (AAQI), and health-risk based AQI (HAQI) to assess the health risks and determine the proportion of people exposed to air pollution. Additionally, on this basis, the AirQ_2.2.3 model was used to quantify the health effects of the pollutants. The results showed that PM₁₀ pollution occurred mainly in spring and winter and was caused by frequent dust storms. PM_2.5 pollution was caused mainly by anthropogenic activities (especially coal-fired heating in winter). Because of a series of government policies and pollutant reduction measures, PM_2.5, SO₂, NO₂, and CO concentrations showed a downward trend during the study period (except for a small increase in the case of NO₂ in some years.). However, O₃ showed high concentrations due to the high intensity of solar radiation in summer and inadequate emission reduction measures. The air quality levels based on their classification were generally higher than the Chinese ambient air quality standard classified by the AQI index. We also found that the higher the AQI index was, the more serious the air pollution classified based on the AAQI and HAQI indices was. The HAQI index could better reflect the impact of pollutants on human health. Based on the HAQI index, 20% of the population in the study area was exposed to polluted air. The total mortality values attributable to PM₁₀, PM_2.5, SO₂, O₃, NO₂, and CO, quantified by the AirQ_2.2.3 model, were 3.00%, 1.02%, 1.00%, 4.22%, 1.57%, and 0.95% (Confidence Interval:95%), respectively; the attributable proportions of mortality for respiratory system and cardiovascular diseases were consistent with the change rule of total mortality, because the number of deaths attributable to the latter was greater than that for the former. According to the exposure reaction curves of pollutants, PM₁₀ and PM_2.5 still showed a large change at high concentrations. However, the tendencies of SO₂, NO₂, CO, and O₃ were more obvious under low concentration exposure, which indicated that the expected mortality rate due to lower air pollution concentrations was much higher than the mortality due to high air pollution concentrations.

Energy Efficiency and Health Efficiency of Old and New EU Member States

Environmental protection and health issues have always been of great concern. This study employed modified Meta-Frontier Dynamic Network Data Envelopment Analysis to explore the environmental pollution effects from energy consumption on the mortality of children and adults, tuberculosis rate, survival rate, and health expenditure efficiencies in 15 old EU states and 13 new EU states from 2010 to 2014. We calculated the overall efficiency scores and technology gap ratios for each old EU and new EU states as well as the efficiencies of non-renewable energy, renewable energy, PM2.5, CO₂, labor, GDP, tuberculosis, child mortality, adult mortality, health expenditure efficiency, and survival efficiency at the health stage. The average annual overall efficiencies of the old EU states are higher than that of the new EU states. Whether in terms of energy efficiencies or health efficiencies, the inputs and outputs of the old EU states are always higher than that of the new EU states. Overall, developing countries in Eastern Europe are lagging behind in terms of energy and health efficiencies. At the same time, the efficiency of child mortality is lower than that of adult mortality, and the efficiency of PM2.5 is higher than that of CO₂ in both old and new EU states.

Fine particulate matter pollution in North China: Seasonal-spatial variations, source apportionment, sector and regional transport contributions

Large areas of mainland China have been suffering frequently from heavy haze pollution during the past years, which feature high concentrations of fine particulate matter (PM_2.5, particulate matters with aerodynamic diameters less than 2.5 μm) and low visibility. Moreover, these areas manifested strong regional complex pollution characteristics, particularly in North China including Beijing and the five surrounding provinces (BSFP). In this study, by using the localized comprehensive emission inventory of BSFP region in 2012 as an input, the Comprehensive Air Quality Model with Extensions-Particulate Matter Source Apportionment Technology (CAMx/PSAT) was used to assess the seasonal variations and source apportionment of PM_2.5 in the highly polluted BSFP region, with a specific focus on the sectoral and sub-regional contributions to PM_2.5 in Beijing during winter and summer. Results showed that the PM_2.5 concentrations of BSFP region was higher in winter than that in summer. And the heavily polluted area in BSFP region shrinked noticeably in summer, compared with winter. As for source apportionment of PM_2.5, residential and remaining industrial sectors constituted the top two sources of PM_2.5 mass concentrations in Beijing. In addition, agricultural source represented a major contributor to ammonium, whereas transportation and power sectors constituted major sources to nitrates. In terms of contributions from sub-regions, the local sources ranked as the dominant contributors to PM_2.5 in Beijing, while the main external contributions originated from the surrounding areas, such as Hebei and Shandong. Results of daily source apportionment to PM_2.5 in Beijing showed that sub-regional long-distance transport became stronger when haze pollution was severe, in which contribution from remaining industrial sector would be higher than that of other periods. The results will allow for an improved understanding of the causes and origins of heavy regional PM_2.5 pollution, and thus will benefit the development of effective joint control policies and identification of key polluting emission categories in North China and ultimately serve as references for other highly polluted megacities in the world.

Temporal variations of six ambient criteria air pollutants from 2015 to 2018, their spatial distributions, health risks and relationships with socioeconomic factors during 2018 in China

Air pollution events occurred frequently in China, and tremendous efforts were devoted to the reduction of air pollution in recent years. Here, analysis of ambient monitoring data of six criteria air pollutants from 367 Chinese cities during 2015-2018, showed that PM_2.5, PM₁₀, SO₂ and CO were reduced significantly by 22.1%, 13.5%, 46.4% and 21.5%, respectively, NO₂ reduction was less significant (6.3%) while O₃ level instead increased over China (13.7%). Spatial distribution, seasonal, monthly and diurnal variations of the air pollutants during 2018, implicated of effective control measures, were discussed in details, especially for the five key densely populated regions of Jing-Jin-Ji (JJJ), Fen Wei Plains (FWP), Yangtze River Delta (YRD), Sichuan Basin (SCB) and Pearl River Delta (PRD). Moreover, excess health risks (ERs) of the six pollutants were estimated for 2018, and such risks was two times higher if the World Health Organization (WHO) air quality guideline rather than Chinese guideline was adopted. PM₁₀ rather than PM_2.5 was the dominant contributor to ERs, and the case with both PM_2.5 and PM₁₀ exceeding threshold values occupied ~1/3 of total days, yet contributed ~2/3 of total ERs. For 2018, the health-risk based air quality index (HAQI) was further calculated by combining health risks from multiple pollutants, and it was found that high HAQI mostly distributed in North China Plain (NCP). ~15%, ~85% and ~95% people in YRD, FWP and JJJ were exposed to polluted air (HAQI > 100), and population-normalized HAQI further added the inequality, JJJ and a small region of SCB had much higher HAQI (>280). Investigations on HAQI with socioeconomic factors show that total population, population density and built-up area presented an inverted U-shape, suggesting existence of Environmental Kuznets Curve (EKC), while a positive relationship was found between HAQI and share of secondary industry. Multiple regression analysis suggested that built-up area was the most prominent factor to HAQI, followed by the gross domestic product (GDP). The findings here demonstrate in great details the current characteristics of air pollution and its associated health risks in China, therefore providing important implications for effective air pollution control strategies in near future for different regions of China.

Spatial Association Pattern of Air Pollution and Influencing Factors in the Beijing-Tianjin-Hebei Air Pollution Transmission Channel: A Case Study in Henan Province

The Beijing–Tianjin–Hebei (BTH) air pollution transmission channel and its surrounding areas are of importance to air pollution control in China. Based on daily data of air quality index (AQI) and air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃) from 2015 to 2016, this study analyzed the spatial and temporal characteristics of air pollution and influencing factors in Henan Province, a key region of the BTH air pollution transmission channel. The result showed that non-attainment days and NAQI were slightly improved at the provincial scale during the study period, whereas that in Hebi, Puyang, and Anyang became worse. PM_2.5 was the largest contributor to the air pollution in all cities based on the number of non-attainment days, but its mean frequency decreased by 21.62%, with the mean occurrence of O₃ doubled. The spatial distribution of NAQI presented a spatial agglomeration pattern, with high-high agglomeration area varying from Jiaozuo, Xinxiang, and Zhengzhou to Anyang and Hebi. In addition, the NAQI was negatively correlated with sunshine duration, temperature, relative humidity, wind speed, and positively to atmospheric pressure and relative humidity in all four clusters, whereas relationships between socioeconomic factors and NAQI differed among them. These findings highlight the need to establish and adjust regional joint prevention and control of air pollution as well as suggest that it is crucially important for implementing effective strategies for O₃ pollution control.

The Energy Efficiency and the Impact of Air Pollution on Health in China

The rapid growth of China's economy in recent years has greatly improved its citizens' living standards, but economic growth consumes many various energy sources as well as produces harmful air pollution. Nitrogen oxides, SO₂ (sulfur dioxide), and other polluting gases are damaging the environment and people's health, with a particular spike in incidences of many air pollution-related diseases in recent years. While there have been many documents discussing China's energy and environmental issues in the past, few of them analyze economic development, air pollution, and residents' health together. Therefore, this study uses the modified undesirable dynamic two-stage DEA (data envelopment analysis) model to explore the economic, environmental, and health efficiencies of 30 provinces in China. The empirical results show the following: (1) Most provinces have lower efficiency values in the health stage than in the production stage. (2) Among the provinces with annual efficiency values below 1, their energy consumption, CO₂ (carbon dioxide), and NOx (nitrogen oxide) efficiency values have mostly declined from 2013 to 2016, while their SO₂ efficiency values have increased (less SO₂ emissions). (3) The growth rate of SO₂ efficiency in 2016 for 10 provinces is much higher than in previous years. (4) The health expenditure efficiencies of most provinces are at a lower level and show room for improvement. (5) In most provinces, the mortality rate is higher, but on a decreasing trend. (6) Finally, as representative for a typical respiratory infection, most provinces have a high level of tuberculosis efficiency, indicating that most areas of China are highly effective at respiratory disease governance.

Temporal and Spatial Features of the Correlation between PM2.5 and O3 Concentrations in China

In recent years, particulate matter of 2.5 µm or less (PM2.5) pollution in China has decreased but, at the same time, ozone (O3) pollution has become increasingly serious. Due to the different research areas and research periods, the existing analyses of the correlation between PM2.5 and O3 have reached different conclusions. In order to clarify the relationship between PM2.5 and O3, this study selected mainland China as the research area, based on the PM2.5 and O3 concentration data of 1458 air quality monitoring stations, and analyzed the correlation between PM2.5 and O3 for different time scales and geographic divisions. Moreover, by combining the characteristics of the pollutants, topography, and climatic features of the study area, we attempted to discuss the causes of the spatial and temporal differences of R-PO (the correlation between PM2.5 and O3). The study found that: (1) R-PO tends to show a positive correlation in summer and a negative correlation in winter, (2) the correlation coefficient of PM2.5 and O3 is lower in the morning and higher in the afternoon, and (3) R-PO also shows significant spatial differences, including north-south differences and coastland-inland differences.

Dynamic Linkages among Economic Development, Energy Consumption, Environment and Health Sustainable in EU and Non-EU Countries

There is a close and important relationship between environmental pollution and public health, and environmental pollution has an important impact on the public health. This study employed the two-stage meta-frontier dynamic network data envelopment analysis (TMDN-DEA) model to explore the environment pollution effects from energy consumption on the mortality of children and adult, tuberculosis rate, survival rate and health expenditure efficiencies in 28 EU countries and 53 non-EU countries from 2010 to 2014. We calculated the overall efficiency scores and the technology gap ratios of each EU and non-EU countries and the efficiencies of input and output variables in the production and health stage. The average overall efficiencies each year in EU countries are higher than in the non-EU countries. But EU countries have higher energy efficiency than non-EU countries, and non-EU countries have higher health efficiency than EU countries. The health expenditure efficiencies in the EU countries are obviously lower than those in non-EU countries. The renewable energy efficiencies are obviously higher than the non-renewable energy efficiencies; PM2.5 efficiencies are obviously higher than the CO₂ efficiencies and the children’s mortality rate efficiencies are higher than the adult’s mortality rate efficiencies for EU countries and non-EU countries. The government management in the EU and non-EU countries should be strengthened to reduce the air pollutant and carbon dioxide emissions and raise energy transformation to the clean energy in renewable energy and improve health efficiencies in medical and health care field.

Dynamic assessment of PM2.5 exposure and health risk using remote sensing and geo-spatial big data

In the past few decades, extensive epidemiological studies have focused on exploring the adverse effects of PM_2.5 (particulate matters with aerodynamic diameters less than 2.5 μm) on public health. However, most of them failed to consider the dynamic changes of population distribution adequately and were limited by the accuracy of PM_2.5 estimations. Therefore, in this study, location-based service (LBS) data from social media and satellite-derived high-quality PM_2.5 concentrations were collected to perform highly spatiotemporal exposure assessments for thirteen cities in the Beijing-Tianjin-Hebei (BTH) region, China. The city-scale exposure levels and the corresponding health outcomes were first estimated. Then the uncertainties in exposure risk assessments were quantified based on in-situ PM_2.5 observations and static population data. The results showed that approximately half of the population living in the BTH region were exposed to monthly mean PM_2.5 concentration greater than 80 μg/m³ in 2015, and the highest risk was observed in December. In terms of all-cause, cardiovascular, and respiratory disease, the premature deaths attributed to PM_2.5 were estimated to be 138,150, 80,945, and 18,752, respectively. A comparative analysis between five different exposure models further illustrated that the dynamic population distribution and accurate PM_2.5 estimations showed great influence on environmental exposure and health assessments and need be carefully considered. Otherwise, the results would be considerably over- or under-estimated.

Emissions of ammonia and hydrogen sulfide from typical dairy barns in central China and major factors influencing the emissions

There are few studies on the concentrations and emission characteristics of ammonia (NH₃) and hydrogen sulfide (H₂S) from Chinese dairy farms. The purpose of this study was to calculate the emission rates of NH₃ and H₂S during summer and to investigate influencing factors for NH₃ and H₂S emissions from typical dairy barns in central China. Eleven dairy barns with open walls and double-slope bell tower roofs from three dairy farms were studied. Five different locations in each barn were sampled both near the floor and at 1.5 m above the floor. Concentrations of NH₃ and H₂S were measured using the Nessler’s reagent spectrophotometry method and the methylene blue spectrophotometric method, respectively. NH₃ concentrations varied between 0.58 and 4.76 mg/m³ with the average of 1.54 mg/m³, while H₂S concentrations ranged from 0.024 to 0.151 mg/m³ with the average of 0.092 mg/m³. The concentrations of NH₃ and H₂S were higher during the day than at night, and were higher near the ground than at the height of 1.5 m, and were higher in the manure area than in other areas. NH₃ and H₂S concentrations in the barns were significantly correlated with nitrogen and sulfur contents in feed and manure (P < 0.05), and with temperature inside the barns (P < 0.05). Calculated emission rates of NH₃ ranged from 13.8 to 41.3 g NH₃/(AU·d), while calculated emission rates of H₂S ranged from 0.15 to 0.46 g H₂S/(AU·d). These results will serve as a starting point for a national inventory of NH₃ and H₂S for the Chinese dairy industry.

Spatiotemporal Characteristics of Air Quality across Weifang from 2014-2018

Air pollution has become a severe threat and challenge in China. Focusing on air quality in a heavily polluted city (Weifang Cty), this study aims to investigate spatial and temporal distribution characteristics of air pollution and identify the influence of weather factors on primary pollutants in Weifang over a long period from 2014-2018. The results indicate the annual Air quality Index (AQI) in Weifang has decreased since 2014 but is still far from the standard for excellent air quality. The primary pollutants are O3 (Ozone), PM10 (Particles with aerodynamic diameter ≤10 µm), and PM2.5 (Particles with aerodynamic diameter ≤10 µm); the annual concentrations of PM10 and PM2.5 show a significant reduction but that of O3 is basically unchanged. Seasonally, PM10 and PM2.5 show a U-shaped pattern, while O3 exhibits inverted U-shaped variations, and different pollutants also present different characteristics daily. Spatially, O3 exhibits a high level in the central region and a low level in the rural areas, while PM10 and PM2.5 are high in the northwest and low in the southeast. Additionally, the concentration of pollutants is greatly affected by meteorological factors, with PM2.5 being negatively correlated with temperature and wind speed, while O3 is positively correlated with the temperature. This research investigated the spatiotemporal characteristics of the air pollution and provided important policy advice based on the findings, which can be used to mitigate air pollution.

Characterization and health risks of criteria air pollutants in Delhi, 2017

Severe air pollution events were observed frequently in north India in recent years especially at its capital, Delhi. Criteria air pollutants data at 10 sites for 2017 in Delhi were analyzed. The results show annual fine particulate matter (PM_2.5) concentrations exceeded the National Ambient Air Quality Standards (NAAQS) of 60 μg/m³ at all sites from 105.51 (site 10) to 143.23 μg/m³ (site 7). Sub-urban sites (site 8, 9 and 10) had lower PM_2.5 concentrations than urban sites. Coarse PM (PM₁₀) and ozone (O₃) were also important with annual averages of 399.56 μg/m³ and 75.69 ppb, respectively. Peak PM_2.5 occurred at the Diwali in early November and Christmas. Only PM₁₀ showed a significant weekly difference with a weekdays/weekends ratio of ∼1.5. PM_2.5/PM₁₀ ratio in episode days with PM_2.5 of >60 μg/m³ was higher than non-episode days. Pearson correlation coefficients show O₃ was negatively related with CO, SO₂, and NO₂, while PM_2.5 was positively related to these pollutants. Analysis of two extreme events from Nov. 6th to Nov. 14th and Dec. 18th to Dec. 26th shows that meteorological conditions with low wind speed and warm temperature kept PM_2.5 concentrations at a high level during these events. Backward trajectory and cluster analysis show the wind coming from northwest of Delhi, where massive anthropogenic emissions were generated, led to high concentrations of air pollutants to Delhi. Health risk analysis reveals that PM_2.5 and PM₁₀ were the two major pollutants threatening public health among the six criteria pollutants.

A Combined Model Based on Feature Selection and WOA for PM2.5 Concentration Forecasting

As people pay more attention to the environment and health, P M 2.5 receives more and more consideration. Establishing a high-precision P M 2.5 concentration prediction model is of great significance for air pollutants monitoring and controlling. This paper proposed a hybrid model based on feature selection and whale optimization algorithm (WOA) for the prediction of P M 2.5 concentration. The proposed model included five modules: data preprocessing module, feature selection module, optimization module, forecasting module and evaluation module. Firstly, signal processing technology CEEMDAN-VMD (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Variational Mode Decomposition) is used to decompose, reconstruct, identify and select the main features of P M 2.5 concentration series in data preprocessing module. Then, AutoCorrelation Function (ACF) is used to extract the variables which have relatively large correlation with predictor, so as to select input variables according to the order of correlation coefficients. Finally, Least Squares Support Vector Machine (LSSVM) is applied to predict the hourly P M 2.5 concentration, and the parameters of LSSVM are optimized by WOA. Two experiment studies reveal that the performance of the proposed model is better than benchmark models, such as single LSSVM model with default parameters optimization, single BP neural networks (BPNN), general regression neural network (GRNN) and some other combined models recently reported.