Improve Air Quality Research Articles

Spatial and temporal changes of air quality in Shandong Province from 2016 to 2022 and model prediction

This study investigates the spatial and temporal dynamics of air quality in Shandong Province from 2016 to 2022. The Air Quality Index (AQI) showed a seasonal pattern, with higher values in winter due to temperature inversions and heating emissions, and lower values in summer aided by favorable dispersion conditions. The AQI improved significantly, decreasing by approximately 39.4 % from 6.44 to 3.90. Coastal cities exhibited better air quality than inland areas, influenced by industrial activities and geographical features. For instance, Zibo's geography restricts pollutant dispersion, resulting in poor air quality. CO levels remained stable, while O3 increased seasonally due to photochemical reactions in summer, with correlation coefficients indicating a strong positive correlation with temperature (r = 0.65). Winter saw elevated NO2 levels linked to heating and vehicular emissions, with an observed increase in correlation with AQI (r = 0.78). PM2.5 and PM10 concentrations were higher in colder months due to heating and atmospheric dust, showing a significant decrease of 45 % and 40 %, respectively, over the study period. Predictive modeling forecasts continued air quality improvements, contingent on sustained policy enforcement and technological advancements. This approach provides a comprehensive framework for future air quality management and improvement.

Air Quality Dynamics in Sichuan Province: Sentinel-5P Data Insights (2019-2023)

This study assesses air pollution in Sichuan Province, China, from January 2019 to December 2023 using Copernicus Sentinel-5P satellite data. The analysis reveals distinct seasonal variations in levels of Carbon Monoxide (CO), Nitrogen Dioxide (NO₂), Sulfur Dioxide (SO₂), and Ozone (O₃), with urban areas experiencing higher concentrations due to industrial and vehicular emissions. CO and O₃ frequently exceeded WHO guidelines, particularly in winter and summer, indicating significant health risks. While most pollutant levels remained within safety limits, the findings highlight the importance of continuous monitoring and targeted mitigation strategies to improve air quality and safeguard public health, especially in urban environments.

Impact of PM2.5 exposure in old age and its interactive effect with smoking on incidence of diabetes

PurposeTo determine the impact of PM2.5 exposure in old age and its interactive effect with smoking on incident diabetes. MethodsA total of 2766 participants aged ≥60 years in China were interviewed at baseline for disease risk factors in 2001–03 and were then followed up for 10 years to document incident diabetes. They were assessed for daily PM2.5 exposure in 2005. Multivariate Cox regression models were used to examine the association of PM2.5 exposure with incident diabetes and interactive effect between PM2.5 and smoking on incident diabetes. ResultsDuring the cohort follow-up, 176 participants developed diabetes. The incidence of diabetes increased with PM2.5 exposure; the multiple-adjusted hazard ratio (HR) of diabetes was 2.27 (95 % CI 1.36–3.77) in participants with PM2.5 at ≥62.0 μg/m3 compared to those at <62.0 μg/m3. There was a significant interaction effect of PM2.5 with smoking on increased risk of diabetes. The adjusted HR for participants exposed to PM2.5 levels ≥62.0 μg/m3 who smoked was 4.39 (95 % CI 1.72–11.21), while for non-smokers it was 1.65 (95 % CI 0.88–3.09), compared to those at <62.0 μg/m3. ConclusionsExposure to PM2.5 in old age was associated with an increased incidence of diabetes and smoking enhanced the impact of PM2.5 on diabetic risk. These findings underscore the urgent need for air quality improvement measures and smoking cessation programs to mitigate the risk of diabetes in aging populations.

COVID-19 lockdown impact on air quality and associated health benefit in two contrasting urban cities in Eastern Indo Gangetic Plain

A key challenge in controlling deteriorating urban air quality is a lack of clear understanding of the regional emissions characteristics and their impact on human health. COVID-19 lockdown provided an opportunity to enhance understanding of background air quality. Towards this, we studied the effect of the lockdown on air pollutants level and associated health benefits in two contrasting urban cities of Eastern IGP, Asansol (industrial) and Kolkata (metropolitan), by analyzing data from 2019 to 2021. The outcomes revealed that the level of exceedance of air pollutants is usually higher in Asansol but significantly decreased in both cities during the lockdown period. Particle concentrations were reduced by 50–70 % compared to Pre-Lockdown and by 20–35 % against the same period in 2019. Kolkata witnessed a higher reduction in PM levels than Asansol. Diurnal variation comparison showed a higher reduction of particle levels during lockdown in the morning at Asansol while in the evening at Kolkata. The health benefits associated with the reduction in PM2.5 concentration were quantified using the BenMAP-CE model, which revealed that improving air quality, like during the lockdown period, would save annually 0.46 and 2.91 deaths per 100,000 persons in Asansol and Kolkata, respectively. Altogether, this study's outcomes provide essential insights to policymakers for regional factors associated to varying air quality and health benefits associated to improvement in air quality.

Assessment of Air Quality Index of Kolkata, Howrah, and 24 Parganas North during COVID- 19 Lockdown

In the course of COVID- 19 pandemic, a nationwide lockdown in India has been imposed from 22nd March 2020 extended to June end, thereafter a partial lockdown was enforced as a precautionary measure to confine the spread of COVID- 19. The anthropogenic activity was restricted during lockdown therefore the pollution level across many cities in India reduced drastically. This eventually led us to analyze the air quality scenario of Kolkata metropolitan city along with suburban areas of North 24 Parganas and Howrah in the state of West Bengal, India. In the present research, the air quality parameters like PM10, PM2.5, SO2, NO2, CO, O3, and NH3 were analyzed the during lockdown phase of 23rd March 2020 to 30th June 2020. A comparative study was done with the air quality data of the pre-lock down phase (March 2019 to 4th March 2020) and an Air Quality Index (AQI) was prepared. During lockdown coal/ fuel consumption was low due to the restriction of vehicle movement and road transport thus carbon emission in the air was less. AQI improved enormously with reduction of SO2 content to &lt;80 %; among other pollutants NO2 and NH3 reduced to &lt;54 % and &lt;91 % in Kolkata, Howrah, and 24 Parganas North. P.M 2.5 drastically reduced in the regions of Kolkata, Howrah, and 24 Parganas North of West Bengal effectively to &lt;81%, &lt;91 %, and &lt;95% respectively. P.M 10 reduced to &lt;75%, &lt;79%, and &lt; 81 % in Kolkata, Howrah, and 24 Parganas North. In Kolkata there was 55% reduction in the level of CO. There was 4 folds reduction of P.M2.5 and P.M10 in Kolkata compared to March- June 2019. About 50 % to 60 % improvement in air quality was identified within 7days of the lockdown. Improvement of air quality during lockdown has benefited the environment and ecology.

Evaluating a Computerized CCS Model Against Current Technologies to Optimize Environmental Conservation for the Patuakhali Power Plant in Bangladesh.

The burgeoning focus on power generation in Bangladesh has spurred the government to embark on ambitious plans for the installation of power plants. Among these developments is the impending operation of a 2*660MW coal-power station in Patuakhali which will operates end of the month in December 2024. There is concern about this plant's carbon-dioxide emission and mitigation in the atmosphere surrounding this area, which may cause a variety of health problems as well as threaten the biodiversity of the plant zone. The proposed technology will not cover all situations and may present some challenges when compared to other technologies. Utilizing an established operational model sanctioned within the country, our assessment revealed an approximate daily carbon emission of 4.806 million kilograms from the power plant. Employing the Sundarbans' sequestration rate, we calculated a carbon tolerance level of around 4.2 million kilograms per day for the plant area. Despite the emission levels being considered marginal, given the Sundarbans' capacity for carbon sequestration, our study highlights the potential of computerized Carbon Capture and Storage (CCS) technology to significantly mitigate emissions, potentially reducing them to near-zero levels. This research also compares a computerized CCS model with exiting model which can optimize environmental conservation by simulating and analyzing the effectiveness of different carbon capture technologies, selecting optimal storage sites, and assessing the lifecycle impact of CCS projects. Among the most notable solutions is carbon capture and storage (CCS) technology, which can cut carbon emissions by over 90%. Furthermore, the incorporation of a computerized system can reduce emissions by over 90% as well as stop CO2 leaks and lessen related risks. It enhances operational efficiency, reduces costs, and supports policy compliance through precise data-driven insights. However, the security of the entire carbon capture, transportation, and storage process is guaranteed by this all-encompassing strategy. Recognizing the Sundarbans' critical role in sustaining a diversity of life and nature, it is crucial to strike a balance between environmental preservation and economic development. If the system is fully integrated and functional, advanced technologies like computerized carbon capture and storage have the potential to minimize carbon emissions to zero. It also offers economic benefits as well as carbon credits, and improves air quality and ocean health by mitigating pollutants and CO2 emissions.

The Role of Community Conversation in Improving Air Quality

The Role of Community Conversation in Improving Air Quality

East African Megacity Air Quality: Rationale and Framework for a Measurement and Modeling Program

Abstract Air pollution in Africa is a significant public health issue responsible for 1.1 million premature deaths annually. Sub-Saharan Africa has the highest rate of population growth and urbanization of any region in the world, with substantial potential for future emission growth and worsening air quality. Accurate and extensive observations of meteorology and atmospheric composition have underpinned successful air pollution mitigation strategies in the Global North, yet Africa in general and East Africa in particular remain among the most sparsely observed regions in the world. This paper is based on the discussion of these issues during two international workshops, one held virtually in the United States in July 2021 and one in Kigali, Rwanda, in January 2023. The workshops were designed to develop a measurement, capacity building, and collaboration strategy to improve air quality-relevant measurements, modeling, and data availability in East Africa. This paper frames the relevant scientific needs and describes the requirements for training and infrastructure development for an integrated observing and modeling strategy that includes partnerships between East African scientists and organizations and their counterparts in the developed world.

Impact of fine particulate pollution exposures on respiratory health in a megacity of Pakistan

Air pollution poses a substantial barrier to global environmental sustainability and citizen well-being. However, there is a lack of research that specifically examines the effects of short-term exposure to PM2.5 and its components on health outcomes in developing nations in Asia, regions often cited as having some of the most severe urban air quality issues globally. The present study evaluated the associations between PM2.5 components and hospital admissions (HA) and emergency room visits (ERV) for respiratory diseases in the megacity of Karachi, Pakistan. We measured PM2.5 constituents, including black carbon (BC) and ionic species (sulfate - SO42−; nitrate - NO3−; and ammonium - NH4+) at two sites (August 2008 to August 2009) in Karachi. The HA and ERV, respiratory disease outcome data, were collected from three local, large tertiary care hospitals. We assessed the lag structure of excess risk (ER) of the pollutants-outcomes association (0–6 single and cumulative lag days) using time-series quasi-Poisson models after adjusting for temperature, humidity, and day of the week. Among a total 13,827 patients, the highest ERs for all respiratory urgent care use (UCU) were observed for PM2.5 (10.3, 95% CI: 2.59%-18.59), NH4+ (9.58%, 95% CI: 1.50%–18.30%), air quality index (9.11%, 95%CI: 2.54%–16.09%) and SO42− (7.26%, 95% CI: 1.03%–13.87%) within 0–4 lag days. Additionally, patients with chronic obstructive pulmonary disease (COPD), tuberculosis (TB), or other pulmonary diseases and older or male patients were more vulnerable to these pollutants. This first study in Pakistan found that PM2.5 and its constituents were associated with respiratory HAs and ERVs for the inhabitants of the megacity of Karachi. These associations varied by different PM constituents, disease subtypes, age, and gender. Our results provide important information to policymakers for developing regulations for improving air quality and public health. Further studies are urgently needed in other developing countries to disentangle the air pollution health effects.

A study on air quality prediction with multiple features based on GCN-LSTM

Abstract Air pollution is closely intertwined with public health. However, air quality forecasting is a very challenging project, and the influencing factors are intertwined. This study focuses on analyzing and forecasting urban air quality from a spatiotemporal perspective, based on various factors that affect air quality. In this paper, a diverse dataset impacting air quality was collected, including pollutant concentrations, meteorological conditions, and traffic flow data. A GCN-LSTM model was developed to thoroughly explore the spatial relationships between different sites within the study area. This paper also conducted forecasts over different time lengths. The experiments revealed that weather data and traffic data can help improve air quality prediction results. The forecasting accuracy for RMSE and MAE were improved by an average of 8.7% and 8.5% in PM2.5, and 12.8% and 11.9% in NO2, respectively. Within the model, the GCN-LSTM model, which considers spatiotemporal features, outperformed single models and proved to be more advantageous in long-term forecasting. The findings of this study contribute to the improvement of air quality prediction effectiveness.

Design and Analysis of Dehumidifier to Improve Air Quality

Compressed air is used for obtaining brake application in which brake pipe and feed pipe run throughout the length of the coach. Brake pipe and feed pipe on consecutive coaches in the train are coupled to one another by means of respective hose couplings to form a continuous air passage from the locomotive to the rear end of the train. Compressed air is supplied to brake pipe and feed pipe from locomotive also the magnitude of braking force increases in steps with the corresponding reduction in brake pipe pressure. So due to brake binding and brake failures due to pressure drop and high moisture rate so there was need of dehumidifier because of less moisturized air. When passed to braking system it will help the braking system and there will be less brake binding and pressure failure in braking system so with the help of dehumidifier, we can reduce moisture content and pass dry air to the braking system and increase good braking effect and decrease maintenance. As per the result of dehumidifier we have decreased moisture content up to 81.08% and decreased maintenance life by 120 days also this dehumidifier is less small in size than the prior one. From obtained moisture content of 37%, we have decreased it to 7%. Also, it is more efficient to replace silica gel easily in this dehumidifier.

Exploring the role of the Internet of Things in green buildings

AbstractThe global energy crisis has been one of the significant challenges for decades, threatening the global economy, and the health of our environment. The government's efforts to enhance the welfare and lifestyle of citizens have been partially undermined by a significant rise in energy intensity, resulting in increased energy consumption. Over the years, researchers have utilized historical energy consumption data to enhance energy efficiency through various technologies. Innovative smart technologies drive energy efficiency, reducing energy usage throughout all areas of the energy industry, from production and supply to consumption. This creates a balance in all sectors and indicates a decrease in energy demand in all areas of building infrastructure. Green buildings that utilize Internet of Things (IoT) technology employ sensors and software to collect data, optimizing, and enhancing building performance. This includes reducing energy and electricity consumption, improving air quality, and optimizing lighting throughout the day. These buildings can contribute to reaching zero‐energy building targets. It becomes challenging to manage green buildings without using centralized control. Therefore, managing and integrating these buildings with intelligent technologies is vital in achieving environmentally friendly management. This study offers a broad overview of the green building concept and explores the use of the green IoT in enhancing services and conserving energy within green buildings. The article aims to deliver an extensive review of green buildings and their advantages, analyze the technology behind the IoT and its integration with solar panels to lower energy consumption, and ultimately identify the challenges present in this area of research.

Ecological benefits of roof gardens and the difference of roof gardens in different regions

As a result of the rapid pace of urbanization today, environmental destruction is outpacing regeneration, and many "urban diseases" are occurring frequently. Therefore, there is a need for a facility that can protect the environment without destroying the original city - roof gardens. This paper focuses on the ecological benefits of rooftop gardens and their application in practical situations. It is found that rooftop gardens can improve air quality, store rainwater, mitigate the heat island effect and protect biodiversity. These effects have well alleviated the problems of urban air pollution, water resource stress, urban heat island effect and destruction of ecological environment. And research has found that there are already many excellent examples of the application of rooftop gardens at home and abroad, helping to confirm that rooftop gardens do indeed have the ecological benefits mentioned above, adding to the feasibility. Rooftop gardens are indispensable in the construction of future cities for the well-being of urban residents.

The impact of hydrogen fuel cell heavy-duty trucks purchase subsidies on air quality.

The pollutant emissions of diesel-powered heavy-duty trucks (HDTs) seriously damage the air quality. The promotion of hydrogen fuel cell HDTs through purchase subsidy policy to reduce emissions has become an important approach to control air pollution. This study focuses on the impact of hydrogen fuel cell HDT purchase subsidies on air quality in the context of China, covering the panel data of 31 Chinese cities from 2014 to 2021 and applying a two-way fixed effects model to analyze the contribution of purchase subsidies and hydrogen refueling station construction subsidies to air quality. Results show that (1) the increase in purchase subsidies could improve the air quality by around 6.1% and there is a lag effect. (2) Purchase subsidies make a larger contribution to air quality compared with construction subsidies. (3) Purchase subsidies can improve air quality by reducing carbon emissions in transport industry. In sight of these results, policy makers should emphasize the implementation of purchase subsidies and hydrogen refueling station construction subsidies and stimulate manufacturers to improve the performance of hydrogen fuel cell so as to contribute more to the environment.

Improvement of Air Quality During Lockdown Period of COVID-19 Pandemic in Kathmandu Valley, Nepal

The Kathmandu Valley is currently Nepal's most hazardous region for human health and environmental sustainability because of increased air pollution and high particulate matter levels. According to multiple studies and observations, Nepal's urban districts saw an improvement in air quality during the COVID-19 lockdown. The Air Quality Index (AQI) is a standard method of informing the public about air pollution levels. The AQI is based on the quantitative value of pollutants' constituent parts, such as particulate matter (PM). Thus, the focus of this study was on how the AQI values change in the Ratna Park suburb of the Kathmandu district in the Kathmandu Valley and how those fluctuations are related to lockdown and non-lockdown times during the COVID-19 pandemic and comparing them to identify crucial information’s. This study shows that during the lockdown, the air quality in the Kathmandu Valley dramatically improved, with average AQI values for PM2.5 and PM10 rising to 21.34 and 64.42 from 50.74 and 106.51, respectively. Furthermore, we investigate the positive correlation between relative humidity, a meteorological component, and air quality.

Enhancing Sustainable Thermal Comfort of Tropical Urban Buildings with Indoor Plants

Rapid urbanization exacerbates the urban heat island effect, raising local temperatures and endangering residents’ health and well-being. The decreasing green spaces resulting from urbanization necessitate global action focused on reducing heat island intensity and addressing heat stress. Urban green infrastructure (UGI) offers solutions for enhanced comfort and reduced pollution through passive methods. Various large-scale UGI projects have been implemented to regulate temperature and improve air quality in urban areas. More research on smaller green spaces is essential to improve the microclimate in space-constrained urban cities. This experimental study examines the thermal effectiveness of potted plants located on balconies of a mid-rise residential building in Chennai, India. The study aims to enlighten balcony greening’s role in reducing heat stress by monitoring temperature and humidity indoors and outdoors, with and without potted plants at similar solar radiation. Potted plants significantly lowered indoor air and surface temperatures by about 3 °C. Thus, balconies offer untapped potential for green interventions that are often unnoticed in tropical climates like India. The challenges in the installation and maintenance of UGI hinder the widespread adoption of UGI even though UGI positively influences residential well-being. The significant findings benefit urban planners and architects, enlightening strategies to enhance urban thermal comfort and mitigate heat stress through small-scale and cost-effective green interventions. This research contributes to sustainable urban development in tropical climates, aligning with several UN Sustainable Development Goals (SDGs), including SDGs 3, 7, 11, 13, and 15.

Impacts of the Chengdu 2021 world university games on NO2 pollution: Implications for urban vehicle electrification promotion

Emissions of nitrogen oxides (NOx) are a dominant contributor to ambient nitrogen dioxide (NO2) concentrations, but the quantitative relationship between them at an intracity scale remains elusive. The Chengdu 2021 FISU World University Games (July 22 to August 10, 2023) was the first world-class multisport event in China after the COVID-19 pandemic which led to a substantial decline in NOx emissions in Chengdu. This study evaluated the impact of variations in NOx emissions on NO2 concentrations at a fine spatiotemporal scale by leveraging this event-driven experiment. Based on ground-based and satellite observations, we developed a data-driven approach to estimate full-coverage hourly NO2 concentrations at 1 km resolution. Then, a random-forest-based meteorological normalization method was applied to decouple the impact of meteorological conditions on NO2 concentrations for every grid cell, the resulting data were then compared with the timely bottom-up NOx emissions. The SHapley-Additive-exPlanation (SHAP) method was employed to delineate the individual contributions of meteorological factors and various emission sources to the changes in NO2 concentrations. According to the full-coverage meteorologically normalized NO2 concentrations, a decrease in NOx emissions and favorable meteorological conditions accounted for 80 % and 20 % of the NO2 reduction, respectively, across Chengdu city during the control period. Within the strict control zone, a 30 % decrease in the meteorologically normalized NO2 concentrations was observed during the control period. The normalized NO2 concentrations demonstrated a strong correlation with NOx emissions (R = 0.96). Based on the SHAP analysis, traffic emissions accounted for 73 % of the reduction in NO2 concentrations, underscoring the significance of traffic control measures in improving air quality in urban areas. This study provides insights into the relationship between NO2 concentrations and NOx emissions using real-world data, which implies the substantial benefits of vehicle electrification for sustainable urban development.

Quantifying embodied energy consumption and air pollutant emissions in China's real estate development in 2000–2020

The real estate industry, an end user and pivotal economic driver worldwide, significantly affects material and energy consumption, and indirectly determines air pollutant emissions. Assessing these variables from the angle of end users is essential to provide a national evaluation strategy for energy consumption and air pollutant emissions, particularly for future policies. As the first step, this study aims to develop a framework to estimate the consumption of building materials and energy, and the resultant embodied pollutant emissions from real estate development in China between 2000 and 2020. Data derived from the framework indicate a rise in building material consumption from 111.8 Mt. in 2000 to 325.1 Mt. in 2020, despite a post-2014 decline due to reduced construction activities. The real estate sector is integral to the demand for key materials, such as steel, cement, and glass, although their relative consumption has decreased within the sector. In detail, energy use in real estate development increased from 57.1 Mtce in 2000 to 134.7 Mtce by 2020, representing 3–5% of China's total energy consumption. A substantial decrease in major pollutant emissions from the real estate occurred from 2010 to 2020 in China, which is attributed to improved control measures and technologies. In addition, a focused regional analysis indicated a developmental shift towards the central and western provinces, emphasizing the need for tailored emission-reduction strategies therein. These findings underscore the substantial role of China's real estate development in material, energy consumption, and pollutant emissions. The insights provided by this study are vital for formulating strategic plans and foundational data to support China's continuous efforts to improve air quality.

Surgical Air Disinfection Technology Leads to Improvements in OR Air Quality.

Surgical Air Disinfection Technology Leads to Improvements in OR Air Quality.

Mitigation of ammonia and methane emissions with manure amendments during storage of cattle slurry.

This study aimed at assessing the efficacy of manure amendments in abating ammonia (NH3) and methane (CH4) emissions during storage. Two experiments were carried out. Experiment 1 was conducted using 20 L of slurry for 98 days. Treatments were: aluminium sulphate (alum), lactogypsum, zeolite, actiglene, ammonium thiosulphate, biochar, dairy processing waste, Digest-IT and control (without amendment). Experiment 2 was conducted using 660 L of slurry in underground storage tanks for 77 days. Treatments were: sulphuric acid, gypsum, biochar and control (without amendment). NH3 measurements for experiment 1 and experiment 2 were conducted using the photoacoustic gas monitor and dynamic chamber techniques, respectively. CH4 was measured using the static chamber technique in both experiments. The effect of amendments on slurry composition was determined at the end of the experiments. Experiment 1 showed a significant reduction in NH3 emissions in the alum (82%), lactogypsum (46%) and zeolite (32%) treatments relative to the control (100.3% total ammoniacal nitrogen (TAN)). CH4 was reduced significantly in the alum (87%), ammonium thiosulphate (64%) and lactogypsum (67%) relative to the control (291.9 g m-2). Experiment 2 showed a significant reduction (32%) in NH3 emissions in the sulphuric acid relative to the control (4.4% TAN). CH4 was reduced significantly in the sulphuric acid (46%), gypsum (39%) and biochar (15%) treatments relative to the control (291.9 g m-2). In general, amendments altered slurry composition such as dry matter, volatile solids, carbon and nitrogen contents at the end of storage. Lactogypsum, alum and sulphuric acid were effective in abating both NH3 and CH4 emissions and can contribute to improving air quality.