Unmanned aerial vehicles equipped with sensor packages to study spatiotemporal variations of air pollutants in industry parks.

Unmanned aerial vehicles (UAVs) equipped with a miniaturized sensor package were developed for aerial observations, which realizes aerial observations affordable to scientists in atmospheric science and achieves aerial measurements in high spatial resolution. UAVs are deployed to a variety of aerial detecting tasks in different scientific scenarios including chemical industry parks (CIPs) with hazardous gases emissions, and some places difficult for humans to reach. In this study, UAV sensing technology was deployed to detect air pollutants in a suburb, a CIP and a natural gas plant, respectively. The effects of atmospheric conditions such as the atmospheric boundary layer height, long-distance transport and atmospheric stability on the spatiotemporal variations of the air pollutants vertical profiles were investigated by the UAV. The UAV with the sensor package was deployed to capture the methane (CH4) leakages in a natural gas plant. The spatiotemporal variations of CH4 in both vertical and horizontal directions studied by UAV were employed to calculate accurate CH4 emissions, which is crucial to reducing the emissions of greenhouse gases. The low-cost UAV sensing technology for air pollutants was developed by Dr. Xiaobing Pang, who was funded by the Newton Fellowship in 2009 and worked in the University of York. This article is part of the theme issue 'Celebrating the 15th anniversary of the Royal Society Newton International Fellowship'.

Short-term effects of air pollutants and meteorological factors on outpatients with allergic airway disease in Ningbo, China, 2015-2021.

OBJECTIVES: The allergic airway disease, such as allergic rhinitis, chronic rhinosinusitis, asthma, is a general term of a range of inflammatory disorders affecting the upper and lower airways and lung parenchyma. This study aimed to investigate the short-term effects of air pollutants and meteorological factors on AAD-related daily outpatient visits. STUDY DESIGN: An ecological study. METHODS: Data on outpatient visits due to AAD (n = 4,554,404) were collected from the platform of the Ningbo Health Information from January 1, 2015 to December 31, 2021. A Quasi-Poisson generalized additive regression model was established to analyze the lag effects of air pollution on daily outpatient visits for AAD. Restricted cubic spline functions were used to explore the potential non-linear relationships between air pollutants and meteorological and daily outpatient visits for AAD. RESULTS: PM2.5, PM10, SO2, NO2, or CO were associated with daily outpatient visits for AAD, and there was a significant increasing trend in the cumulative lag effects. SO2 had the largest effect at Lag07, with a 25.3% (95% CI: 21.6%-29.0%) increase in AAD for every 10 µg/m3 increase in exposure concentration. Subgroup analysis showed that the 0-18 years old age group had the strongest effects, especially for AR, and all effects were stronger in the cold season. CONCLUSIONS: Given that patients aged 0-18 are more susceptible to environmental changes, protective measures specifically for children should be taken during dry and cold weather conditions with poor air quality.

Atmospheric nitrogen dioxide suppresses the activity of phytochrome interacting factor 4 to suppress hypocotyl elongation.

MAIN CONCLUSION: Ambient concentrations of atmospheric nitrogen dioxide (NO2) inhibit the binding of PIF4 to promoter regions of auxin pathway genes to suppress hypocotyl elongation in Arabidopsis. Ambient concentrations (10-50 ppb) of atmospheric nitrogen dioxide (NO2) positively regulate plant growth to the extent that organ size and shoot biomass can nearly double in various species, including Arabidopsis thaliana (Arabidopsis). However, the precise molecular mechanism underlying NO2-mediated processes in plants, and the involvement of specific molecules in these processes, remain unknown. We measured hypocotyl elongation and the transcript levels of PIF4, encoding a bHLH transcription factor, and its target genes in wild-type (WT) and various pif mutants grown in the presence or absence of 50 ppb NO2. Chromatin immunoprecipitation assays were performed to quantify binding of PIF4 to the promoter regions of its target genes. NO2 suppressed hypocotyl elongation in WT plants, but not in the pifq or pif4 mutants. NO2 suppressed the expression of target genes of PIF4, but did not affect the transcript level of the PIF4 gene itself or the level of PIF4 protein. NO2 inhibited the binding of PIF4 to the promoter regions of two of its target genes, SAUR46 and SAUR67. In conclusion, NO2 inhibits the binding of PIF4 to the promoter regions of genes involved in the auxin pathway to suppress hypocotyl elongation in Arabidopsis. Consequently, PIF4 emerges as a pivotal participant in this regulatory process. This study has further clarified the intricate regulatory mechanisms governing plant responses to environmental pollutants, thereby advancing our understanding of how plants adapt to changing atmospheric conditions.

The association between air pollutant exposure and cerebral small vessel disease imaging markers with modifying effects of PRS-defined genetic susceptibility.

Studies have highlighted a possible link between air pollution and cerebral small vessel disease (CSVD) imaging markers. However, the exact association and effects of polygenic risk score (PRS) defined genetic susceptibility remains unclear. This cross-sectional study used data from the UK Biobank. Participants aged 40-69 years were recruited between the year 2006 and 2010. The annual average concentrations of NOX, NO2, PM2.5, PM2.5-10, PM2.5 absorbance, and PM10, were estimated, and joint exposure to multiple air pollutants was reflected in the air pollution index (APEX). Air pollutant exposure was classified into the low (T1), intermediate (T2), and high (T3) tertiles. Three CSVD markers were used: white matter hyper-intensity (WMH), mean diffusivity (MD), and fractional anisotropy (FA). The first principal components of the MD and FA measures in the 48 white matter tracts were analysed. The sample consisted of 44,470 participants from the UK Biobank. The median (T1-T3) concentrations of pollutants were as follows: NO2, 25.5 (22.4-28.7) µg/m3; NOx, 41.3 (36.2-46.7) µg/m3; PM10, 15.9 (15.4-16.4) µg/m3; PM2.5, 9.9 (9.5-10.3) µg/m3; PM2.5 absorbance, 1.1 (1.0-1.2) per metre; and PM2.5-10, 6.1 (5.9-6.3) µg/m3. Compared with the low group, the high group's APEX, NOX, and PM2.5 levels were associated with increased WMH volumes, and the estimates (95 %CI) were 0.024 (0.003, 0.044), 0.030 (0.010, 0.050), and 0.032 (0.011, 0.053), respectively, after adjusting for potential confounders. APEX, PM10, PM2.5 absorbance, and PM2.5-10 exposure in the high group were associated with increased FA values compared to that in the low group. Sex-specific analyses revealed associations only in females. Regarding the combined associations of air pollutant exposure and PRS-defined genetic susceptibility with CSVD markers, the associations of NO2, NOX, PM2.5, and PM2.5-10 with WMH were more profound in females with low PRS-defined genetic susceptibility, and the associations of PM10, PM2.5, and PM2.5 absorbance with FA were more profound in females with higher PRS-defined genetic susceptibility. Our study demonstrated that air pollutant exposure may be associated with CSVD imaging markers, with females being more susceptible, and that PRS-defined genetic susceptibility may modify the associations of air pollutants.

Multi-sensor monitoring and analysis of indoor pollutant emissions in response to laser cutter operating conditions.

This study analyzed pollutant emissions from laser cutters used in modeling in a laboratory, which can have harmful effects on indoor air quality and health. Four conditions were tested: material thickness, laser cutter strength, minimum strength per thickness, and air purifier level. Four pollutants were analyzed: PM2.5, HCHO, VOCs, and CO2. The study found that the emissions of PM2.5, HCHO, and VOCs increased with paperboard thickness, while CO2 emissions were not significant. PM2.5 was more affected by laser cutting strength, while HCHO and VOCs were more affected by paperboard thickness. Additionally, we analyzed the PM2.5 emission rates based on the thickness of the paperboard and the laser cutting strength. Therefore, emission rates based on thickness and laser cutting strength ranged from 7275 to 18,783 µg/min. The air purifier significantly reduced PM2.5 but not HCHO and VOCs. To reduce these gaseous pollutants, combining mechanical ventilation or using an air purifier with a filter that adsorbs HCHO and VOCs is effective. This study highlights the importance of considering laser cutters as a potential source of indoor air pollutants and implementing measures to mitigate their harmful effects.

Association between short-term exposure to ambient air pollutants and the risk of hospital visits for acute upper respiratory tract infections among adults: a time-series study in Ningbo, China.

OBJECTIVES: Acute upper respiratory tract infections (AURTIs) are prevalent in the general population. However, studies on the association of short-term exposure to air pollution with the risk of hospital visits for AURTIs in adults are limited. This study aimed to explore the short-term exposure to air pollutants among Chinese adults living in Ningbo. METHODS: Quasi-Poisson time serious regressions with distributed lag non-linear models (DLNM) were applied to explore the association between ambient air pollution and AURTIs cases. Patients ≥ 18 years who visit three hospitals, being representative for urban, urban-rural junction and rural were included in this retrospective study. RESULTS: In total, 104,441 cases with AURTIs were enrolled in hospital during 2015-2019. The main results showed that particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5), nitrogen dioxide (NO2) and nitrogen dioxide (SO2), were positively associated to hospital visits for AURTIs, except for nitrogen dioxide (O3), which was not statistically significant. The largest single-lag effect for PM2.5 at lag 8 days (RR = 1.02, 95%CI: 1.08-1.40), for NO2 at lag 13 days (RR = 1.03, 95%CI: 1.00-1.06) and for SO2 at lag 5 days (RR = 1.27, 95%CI: 1.08-1.48), respectively. In the stratified analysis, females, and young adults (18-60 years) were more vulnerable to PM2.5 and SO2 and the effect was greater in rural areas and urban-rural junction. CONCLUSIONS: Exposure to ambient air pollution was significantly associated with hospital visits for AURTIs. This study provides epidemiological evidence for policymakers to control better air quality and establish an enhanced system of air pollution alerts.

Biomass Ppower generation: A pathway to carbon neutrality.

In light of the pressing need to reduce carbon emissions, the biomass power generation industry has gained significant attention and has increasingly become a crucial focus in China. However, there are still considerable gaps in the historical background, status, and prospects of biomass power generation. Herein, the historical and current status of biomass power generation in China are systematically reviewed, with a particular emphasis on supportive policies, environmental impacts, and future projections. By 2022, the newly installed capacity for biomass power generation reached 3.34 MW with a total installed capacity of 41 MW. The power produced from biomass power generation is 182.4 billion kWh in China. The total installed capacity and generated power in 2022 were 1652 and 1139 folds higher than in 2006 when the first biomass generation plant was established. However, disparities in the distribution of biomass resources and power generation were observed. Key drivers of the industry development include tax, finance, and subsidy policies. Under the implementation of the 14th Five-Year Plan for renewable energy development and the goal of carbon neutrality, biomass power generation may achieve great success through more targeted policy support and advanced technologies that reduce air pollutant emissions. If combined with Bioenergy with Carbon Capture and Storage (BECCS) technology, biomass power generation will make its contribution to carbon neutrality in China.

The effects of meteorological factors and air pollutants on the incidence of tuberculosis in people living with HIV/AIDS in subtropical Guangxi, China.

BACKGROUND: Previous studies have shown the association between tuberculosis (TB) and meteorological factors/air pollutants. However, little information is available for people living with HIV/AIDS (PLWHA), who are highly susceptible to TB. METHOD: Data regarding TB cases in PLWHA from 2014 to2020 were collected from the HIV antiviral therapy cohort in Guangxi, China. Meteorological and air pollutants data for the same period were obtained from the China Meteorological Science Data Sharing Service Network and Department of Ecology and Environment of Guangxi. A distribution lag non-linear model (DLNM) was used to evaluate the effects of meteorological factors and air pollutant exposure on the risk of TB in PLWHA. RESULTS: A total of 2087 new or re-active TB cases were collected, which had a significant seasonal and periodic distribution. Compared with the median values, the maximum cumulative relative risk (RR) for TB in PLWHA was 0.663 (95% confidence interval [CI]: 0.507-0.866, lag 4 weeks) for a 5-unit increase in temperature, and 1.478 (95% CI: 1.116-1.957, lag 4 weeks) for a 2-unit increase in precipitation. However, neither wind speed nor PM10 had a significant cumulative lag effect. Extreme analysis demonstrated that the hot effect (RR = 0.638, 95%CI: 0.425-0.958, lag 4 weeks), the rainy effect (RR = 0.285, 95%CI: 0.135-0.599, lag 4 weeks), and the rainless effect (RR = 0.552, 95%CI: 0.322-0.947, lag 4 weeks) reduced the risk of TB. Furthermore, in the CD4(+) T cells < 200 cells/µL subgroup, temperature, precipitation, and PM10 had a significant hysteretic effect on TB incidence, while temperature and precipitation had a significant cumulative lag effect. However, these effects were not observed in the CD4(+) T cells ≥ 200 cells/µL subgroup. CONCLUSION: For PLWHA in subtropical Guangxi, temperature and precipitation had a significant cumulative effect on TB incidence among PLWHA, while air pollutants had little effect. Moreover, the influence of meteorological factors on the incidence of TB also depends on the immune status of PLWHA.

Relationship of long-term exposure to air pollutant mixture with metabolic-associated fatty liver disease and subtypes: A retrospective cohort study of the employed population of Southwest China.

BACKGROUND: While evidence suggests that PM2.5 is associated with overall prevalence of Metabolic (dysfunction)-Associated Fatty Liver Disease (MAFLD), effects of comprehensive air pollutant mixture on MAFLD and its subtypes remain unclear. OBJECTIVE: To investigate individual and joint effects of long-term exposure to comprehensive air pollutant mixture on MAFLD and its subtypes. METHODS: Data of 27,699 participants of the Chinese Cohort of Working Adults were analyzed. MAFLD and subtypes, including overweight/obesity, lean, and diabetes MAFLD, were diagnosed according to clinical guidelines. Concentrations of NO3-, SO42-, NH4+, organic matter (OM), black carbon (BC), PM2.5, SO2, NO2, O3 and CO were estimated as a weighted average over participants' residential and work addresses for the three years preceding outcome assessment. Logistic regression and weighted quantile sum regression were used to estimate individual and joint effects of air pollutant mixture on presence of MAFLD. RESULTS: Overall prevalence of MAFLD was 26.6 % with overweight/obesity, lean, and diabetes MAFLD accounting for 92.0 %, 6.4 %, and 1.6 %, respectively. Exposure to SO42-, NO3-, NH4+, BC, PM2.5, NO2, O3and CO was significantly associated with overall MAFLD, overweight/obesity MAFLD, or lean MAFLD in single pollutant models. Joint effects of air pollutant mixture were observed for overall MAFLD (OR = 1.10 [95 % CI: 1.03, 1.17]), overweight/obesity (1.09 [1.02, 1.15]), and lean MAFLD (1.63 [1.28, 2.07]). Contributions of individual air pollutants to joint effects were dominated by CO in overall and overweight/obesity MAFLD (Weights were 42.31 % and 45.87 %, respectively), while SO42- (36.34 %), SO2 (21.00 %) and BC (12.38 %) were more important in lean MAFLD. Being male, aged above 45 years and smoking increased joint effects of air pollutant mixture on overall MAFLD. CONCLUSIONS: Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO42- were associated with lean MAFLD.

Self-reported exposure to dust and diesel exhaust, respiratory symptoms, and use of respiratory protective equipment among Arctic miners.

Arctic miners face significant risks from diesel exhaust and dust exposure, potentially leading to adverse respiratory health. Employers must limit harmful exposures, using personal protective equipment (PPE) as a last line of defense. This study explored the association between reported respiratory exposure and symptoms, and PPE training and usage. Data from the MineHealth study (2012-2014) included a total of 453 Arctic open pit miners in Norway, Sweden, and Finland. Participants answered questions on exposure to dust and diesel exhaust, respiratory symptoms, and PPE use, in addition to age, gender, BMI, smoking, and self-rated health. Estimated exposure to dust was common, reported by 91%, 80%, and 82% and that of diesel exhaust by 84%, 43%, and 47% of workers in Sweden, Finland, and Norway, respectively. Reported dust exposure was significantly related to respiratory symptoms (OR 2.2, 95% CI 1.3-3.7), diesel exposure increased the occurrence of wheezing (OR 2.6, 95% CI 1.3-5.4). PPE use varied between the studied mines. Non-use was common and related to reduced visibility, wetness, skin irritation and fogging of the respiratory PPE. Future research should employ more precise exposure assessment, respiratory function as well as explore the reasons behind the non-compliance of PPE use.

How to effectively achieve air pollutant reduction and carbon mitigation in China's industrial sector? A study based on decomposition analysis and scenario simulation.

Reducing air pollutant and carbon emissions in the industrial sector is crucial for the ecological civilization construction in China. In this study, we first employ the generalized Divisia index method to analyze the driving factors of industrial CO2 and SO2 emissions, incorporating fixed asset investment and R&D input. The key sub-sectors that exert significant impact on emissions of the whole industrial sector are identified. And then, scenario analysis and Monte Carlo simulation are utilized to predict future trends and potential for reducing CO2 and SO2 emissions. Furthermore, the carbon peaking time of the industrial sub-sectors is investigated. The results indicate that fixed asset investment and R&D input both have played positive roles in CO2 and SO2 emissions. Emission reduction is mainly driven by investment emission intensity, output emission intensity, and R&D emission intensity. Sub-sectors S09, S10, S11, S12, and S18 present substantial potential for reducing air pollutant and carbon emissions. Although SO2 emissions from the industrial sector are projected to decrease in the future, the peak of CO2 emissions have not been reached. The carbon peak time for the whole industrial sector is predicted in 2025, with the peak of 7892.33 Mt. The five key sub-sectors are anticipated to reach the respective carbon emission peaks at different times. Therefore, to effectively implement industrial air pollutant and carbon reduction, the role of fixed asset investment and R&D input should be fully utilized, and high-energy consumption and high-emission sub-sectors should be prioritized for action.

[Coordinated Control of Carbon Emission Reduction and Air Quality Improvement in the Industrial Sector in Hunan Province].

Climate warming and air pollution are the main environmental problems in China. This study used China's Carbon Accounting Database, energy economic model, and air quality model to analyze the potential carbon emission peaking path and synergistic air quality improvement gain in the industrial sector in Hunan Province. Based on China's Carbon Accounting Database and the local industry/energy statistical yearbooks in Hunan, the total CO2 emissions in Hunan Province in 2019 were 310.6 Mt, of which the industrial sector accounted for over 70% of the emissions, mainly from the production and supply of electricity, steam, and heat; the production of non-metallic minerals; and the smelting and pressing of ferrous metals. Three potential industrial carbon emission peaking scenarios were analyzed using the LEAP energy economic model, including the business-as-usual scenario (peaking by 2030), moderate emission reduction scenario (peaking by 2028), and aggressive emission reduction scenario (peaking by 2025), by employing different economic growth rates, energy technology progress, and energy structures of the industrial sector. Furthermore, by combining the anthropogenic air pollutant emission inventory and the regional air quality model WRF-Chem, we analyzed the air quality improvement associated with various carbon emission peak paths. The results showed that the annual mean concentrations of major air pollutants had decreased in the three scenarios, especially in the Chang-Zhu-Tan Region. The aggressive emission reduction scenario was the most effective scenario, followed by the moderate emission reduction scenario and the business-as-usual scenario. Manufacturing was the sector with the most significant synergistic effect of pollution and carbon reduction. When carbon emission peaks were achieved, the annual average concentrations of PM2.5 and PM10 in Hunan Province could be synergistically reduced by 0.6-1.8 µg·m-3 and 1.8-8.9 µg·m-3, respectively. Our findings offer important insights into carbon emission peaking and can provide useful information for potential mitigation actions.

Influence of boundary layer jets on the vertical distribution of ozone in Guangdong, China.

The planetary boundary layer (PBL) characteristics during ozone (O3) episodes in China have been extensively studied; however, knowledge of the impact of boundary layer jets (BLJs) on O3 vertical distribution is limited. This study conducted a field campaign from 1 to 8 December 2020 to examine the vertical structure of the O3 concentration and wind velocity within the boundary layer at two sites (Foshan: FS, Maoming: MM) in Guangdong. Utilising lidar observations and the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), distinct spatial distribution patterns of O3 over FS and MM influenced by BLJs were identified. The BLJs at both locations exhibited pronounced diurnal variations with a nocturnal maximum exceeding 11 m/s at a height of approximately 500 m. The nocturnal enhancement of BLJs resulted from inertial oscillations coupled with diurnal thermal forcing over sloping terrain. A stronger BLJ at FS induced an evident uplift of O3 and the prevailing northeasterly wind facilitated the transport of O3 in the nocturnal residual layer from FS to MM. After sunrise, surface heating and the development of the PBL caused the air mass with elevated O3 levels in the residual layer to descend to ground level. At MM, calm surface winds, a weaker BLJ at 500 m height, and strong downdrafts collectively contributed to a significant increase in surface O3 concentration in subsequent days. These findings contribute to our understanding of the interactions between BLJs and variations in surface air pollutant concentrations, thereby providing important insights for future regional emissions control measures.

A decreased impact of air pollution on hospital pneumonia visits during COVID-19 outbreak in northeastern Thailand.

Background: The coronavirus disease 2019 (COVID-19) pandemic had effects on changes in people, society, and pollutant sources. This was a unique research opportunity to assess the effects on the risk of pneumonia resulted from the changes in air pollution and personal hygiene regarding city lockdown. Methods: This study, we estimated time-series relative risks (RRs) of pneumonia (n=94,288) associated with PM10, PM2.5, NO2, and O3 in Khon Kaen province and its vicinity, using Poison regression with generalized additive model and compared air pollutant-associated risk of pneumonia before vs. during the COVID-19 outbreak [2018-2021]. Results: During the COVID-19 period, pneumonia cases, PM2.5, PM10, and NO2 levels were lower than those before the COVID-19 but the O3 level was significantly higher. The single-pollutant analyses showed that the increase in PM10, PM2.5, and NO2 were significantly associated with pneumonia risks at single-day lag 0 in the earlier two years (2018-2019). For multi-pollutant analyses, there were higher RRs in PM2.5 at lag 0 [RR =1.078, 95% confidence interval (CI): 1.004 to 1.157], lag 4 (RR =1.054, 95% CI: 1.011 to 1.098) and lag 5 (RR =1.090, 95% CI: 1.021 to 1.165) and for all cumulative-day lags, greatest was at lag 0-5 (RR =1.314, 95% CI: 1.200 to 1.439) before the COVID-19 period while there were lower pneumonia RRs of a 10-µg/m3 increase in PM2.5 at single-day lag 1 (RR =1.064, 95% CI: 1.002 to 1.130) and for all cumulative-day lags, greatest was at lag 0-5 (RR =1.201, 95% CI: 1.073 to 1.344) during the COVID-19 outbreak. Multi-pollutant of NO2 significantly increased pneumonia risk in cumulative day exposure before the COVID-19 outbreak at lag 0-3 (RR =1.050, 95% CI: 1.001 to 1.100). It was significantly greater than that risk during the outbreak. Conclusions: This study revealed that the lockdown measures to control COVID-19 were effective in improving air quality and lowering associated pneumonia risk. These findings would help raise awareness about measures and policies to preserve the air quality to increase respiratory health benefits.

Air quality and health benefits for different heating decarbonization pathways in China.

The urgent need for decarbonization in China's heating system, comprised of approximately one hundred thousand boilers, is imperative to meet climate and clean air objectives. To formulate national and regional strategies, we developed an integrated model framework that combines a facility-level emission inventory, the Community Multiscale Air Quality (CMAQ) model, and the Global Exposure Mortality Model (GEMM). We then explore the air quality and health benefits of alternative heating decarbonization pathways, including the retirement of coal-fired industrial boilers (CFIBs) for replacement with grid-bound heat supply systems, coal-to-gas conversion, and coal-to-biomass conversion. The gas replacement pathway shows the greatest potential for reducing PM2.5 concentration by 2.8 (2.3-3.4) µg/m3 by 2060, avoiding 23,100 (19,600-26,500) premature deaths. In comparison, the biomass replacement pathway offers slightly lower environmental and health benefits, but is likely to reduce costs by approximately two-thirds. Provincially, optimal pathways vary - Xinjiang, Sichuan, and Chongqing favor coal-to-gas conversion, while Shandong, Henan, Hebei, Inner Mongolia, and Shanxi show promise in CFIBs retirement. Henan leads in environmental and health benefits. Liaoning, Heilongjiang, and Jilin, rich in biomass resources, present opportunities for coal-to-biomass conversion.

Electrostatic particle ionization for suppressing air pollutants in cage-free layer facilities.

The increasing demand for cage-free (CF) poultry farming raises concern regarding air pollutant emissions in these housing systems. Previous studies have indicated that air pollutants such as particulate matter (PM) and ammonia (NH3) pose substantial risks to the health of birds and workers. This study aimed to evaluate the efficacy of electrostatic particle ionization (EPI) technology with different lengths of ion precipitators in reducing air pollutants and investigate the relationship between PM reduction and electricity consumption. Four identical CF rooms were utilized, each accommodating 175 hens of 77 wk of age (WOA). A Latin Square Design method was employed, with 4 treatment lengths: T1 = control (0 m), T2 = 12 ft (3.7 m), T3 = 24 ft (7.3 m), and T4 = 36 ft (11.0 m), where room and WOA are considered as blocking factors. Daily PM concentrations, temperature, and humidity measurements were conducted over 24 h, while NH3 levels, litter moisture content (LMC), and ventilation were measured twice a week in each treatment room. Statistical analysis involved ANOVA, and mean comparisons were performed using the Tukey HSD method with a significance level of P ≤ 0.05. This study found that the EPI system with longer wires reduced PM2.5 concentrations (P ≤ 0.01). Treatment T2, T3, and T4 led to reductions in PM2.5 by 12.1%, 19.3%, and 31.7%, respectively, and in small particle concentrations (particle size >0.5 µm) by 18.0%, 21.1%, and 32.4%, respectively. However, no significant differences were observed for PM10 and large particles (particle size >2.5 µm) (P < 0.10), though the data suggests potential reductions in PM10 (32.7%) and large particles (33.3%) by the T4 treatment. Similarly, there was no significant impact of treatment on NH3 reduction (P = 0.712), possibly due to low NH3 concentration (<2 ppm) and low LMC (<13%) among treatment rooms. Electricity consumption was significantly related to the length of the EPI system (P ≤ 0.01), with longer lengths leading to higher consumption rates. Overall, a longer-length EPI corona pipe is recommended for better air pollutant reduction in CF housing. Further research should focus on enhancing EPI technology, assessing cost-effectiveness, and exploring combinations with other PM reduction strategies.

The joint effect of cumulative doses for outdoor air pollutants exposure in early life on asthma and wheezing among young children.

BACKGROUND: Constrained by no proper way to assess cumulative exposure, the joint effect of air pollution cumulative exposure doses on childhood asthma and wheezing (AW) was not understood. OBJECTIVE: To assess the association between cumulative exposure to multiple air pollutants in early life and childhood AW. METHODS: We designed a nested case-control study based on the birth cohort in Jinan City. Children with AW followed up within 2 years after birth were treated as cases, and non-cases in this cohort were treated as the control source population, and the propensity score matching method was used to match each case to 5 controls. We calculated the individual cumulative outdoor exposure doses for each period using an inverse distance weighted model, alongside the complex Simpson's formula, accounting for outdoor time and respiratory volume. The Least absolute shrinkage and selection operator (Lasso) regression was performed to screen for covariates. To analyze the joint effects of pollutants, we employed the weighted quantile sum (WQS) regression model in conjunction with conditional logistic regression. RESULTS: 84 cases and 420 controls were included in this study. The odds ratio (OR) with 95% confidence interval (CI) of the impact of cumulative exposure (mg/m3) after birth on childhood AW was 1.78 (1.15-2.74) for SO2, 1.69 (1.11-2.57) for NO2, and 1.65 (1.09-2.52) for PM2.5, respectively. Furthermore, with each 25th percentile increase in the WQS index, the overall risk of cumulative doses for six pollutants exposure after birth on AW increased by an adjusted OR of 1.10 (1.03, 1.18), and SO2, PM2.5, and NO2 contributed the most to the WQS index. However, no statistically significant association was found between cumulative exposure to all pollutants before birth and childhood AW. CONCLUSIONS: There was a joint effect of the cumulative exposure dose of outdoor air pollutants after birth on AW in children aged 0-2 years. And traffic-related pollutants (SO2, PM2.5, and NO2) make a greater contribution to the joint effect.

Air pollutant emissions caused by receiving international industrial transfer in Southeast Asian developing countries from 1990 to 2018.

Receiving international industrial transfer (mainly foreign direct investment, FDI) is extremely important for economic development but also brings negative environmental impacts for Southeast Asian developing countries (SEADCs). Due to relatively low labor costs and large market potential, SEADCs have become an attractive destination for industrial transfer after China, while studies were far from sufficient on the associated air pollutant emissions that would worsen air quality and threaten human health. We develop an exploratory framework to estimate the long-term trends of relevant air pollutant emissions in eight major SEADCs, including Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Thailand, and Vietnam. During 1990-2018, the emissions generally show a fluctuating upward trend and increased significantly in Cambodia, Laos, Philippines, and Vietnam. The total emissions of CO, NMVOC, SO2, NOX, PM2.5, and NH3 from the eight SEADCs increased from 19.0, 4.3, 3.6, 1.5, 0.5, and 0.4 kilotons (kt) to 391.6, 260.9, 271.1, 182.4, 48.4, and 12.2 kt, respectively. The emission growth in almost all SEADCs accelerated after 2008 and faster than FDI growth. The disparities in emissions among SEADCs basically grew first and then declined to a level lower than that of 1990, but generally exceeded the disparities in FDI. Productivity gain and emission intensity decrease primarily caused the emission growth and reduction, respectively. Relatively small reductions in emission intensity are found for NOX and SO2. In general, most SEADCs have utilized FDI for economic development without sufficient efforts on air pollutant emission controls. Our outcomes can inform the formulation and optimization of relevant policies reconciling economic development and air quality improvement in SEADCs.

Exploring the spatiotemporal relationship between influenza and air pollution in Fuzhou using spatiotemporal weighted regression model.

Air pollution has become a significant concern for human health, and its impact on influenza, has been increasingly recognized. This study aims to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza and to confirm a better method for infectious disease surveillance. Spearman correlation coefficient was used to evaluate the correlation between air pollution and the influenza case counts. VIF was used to test for collinearity among selected air pollutants. OLS regression, GWR, and STWR models were fitted to explore the potential spatiotemporal relationship between air pollution and influenza. The R2, the RSS and the AICc were used to evaluate and compare the models. In addition, the DTW and K-medoids algorithms were applied to cluster the county-level time-series coefficients. Compared with the OLS regression and GWR models, STWR model exhibits superior fit especially when the influenza outbreak changes rapidly and is able to more accurately capture the changes in different regions and time periods. We discovered that identical air pollutant factors may yield contrasting impacts on influenza within the same period in different areas of Fuzhou. NO2 and PM10 showed opposite impacts on influenza in the eastern and western areas of Fuzhou during all periods. Additionally, our investigation revealed that the relationship between air pollutant factors and influenza may exhibit temporal variations in certain regions. From 2013 to 2019, the influence coefficient of O3 on influenza epidemic intensity changed from negative to positive in the western region and from positive to negative in the eastern region. STWR model could be a useful method to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza in geospatial processes. The research findings emphasize the importance of considering spatiotemporal heterogeneity when studying the relationship between air pollution and influenza.