Regional air quality prediction models using the knowledge－based system approach

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Block Incremental Dense Tucker Decomposition with Application to Spatial and Temporal Analysis of Air Quality Data

How can we efficiently store and mine dynamically generated dense tensors for modeling the behavior of multidimensional dynamic data?Much of the multidimensional dynamic data in the real world is generated in the form of time-growing tensors.For example,air quality tensor data consists of multiple sensory values gathered from wide locations for a long time.Such data,accumulated over time,is redundant and consumes a lot ofmemory in its raw form.We need a way to efficiently store dynamically generated tensor data that increase over time and to model their behavior on demand between arbitrary time blocks.To this end,we propose a Block IncrementalDense Tucker Decomposition(BID-Tucker)method for efficient storage and on-demand modeling ofmultidimensional spatiotemporal data.Assuming that tensors come in unit blocks where only the time domain changes,our proposed BID-Tucker first slices the blocks into matrices and decomposes them via singular value decomposition(SVD).The SVDs of the time×space sliced matrices are stored instead of the raw tensor blocks to save space.When modeling from data is required at particular time blocks,the SVDs of corresponding time blocks are retrieved and incremented to be used for Tucker decomposition.The factor matrices and core tensor of the decomposed results can then be used for further data analysis.We compared our proposed BID-Tucker with D-Tucker,which our method extends,and vanilla Tucker decomposition.We show that our BID-Tucker is faster than both D-Tucker and vanilla Tucker decomposition and uses less memory for storage with a comparable reconstruction error.We applied our proposed BID-Tucker to model the spatial and temporal trends of air quality data collected in South Korea from 2018 to 2022.We were able to model the spatial and temporal air quality trends.We were also able to verify unusual events,such as chronic ozone alerts and large fire events.

Mapping Air Quality Using Remote Sensing Technology: A Case Study of Nairobi County

Nairobi County experiences rapid industrialization and urbanization that contributes to the deteriorating state of air quality, posing a potential health risk to its growing population. Currently, in Nairobi County, most air quality monitoring stations use low-cost, inaccurate monitors prone to defects. The study’s objective was to map Nairobi County’s air quality using freely available remotely sensed imagery. The Air Pollution Index (API) formula was used to characterize the air quality from cloud-free Landsat satellite images i.e., Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI from Google Earth Engine. The API values were computed based on vegetation indices namely NDVI, TVI, DVI, and the SWIR1 and NIR bands on the QGIS platform. Qualitative accuracy assessment was done using sample points drawn from residential, industrial, green spaces, and traffic hotspot categories, based on a passive-random sampling technique. In this study, Landsat 5 API imagery for 2010 provided a reliable representation of local conditions but indicated significant pollution in green spaces, with recorded values ranging from -143 to 334. The study found that Landsat 7 API imagery in 2002 showed expected results with the range of values being -55 to 287, while Landsat 8 indicated high pollution levels in Nairobi. The results emphasized the importance of air quality factors in API calibration and the unmatched spatial coverage of satellite observations over ground-based monitoring techniques. The study recommends the recalibration of the API formula for characteristic regions, exploring newer satellite sensors like those onboard Landsat 9 and Sentinel 2, and involving key stakeholders in a discourse to develop a suitable Kenyan air quality index.

Air Quality Assessment of Ubeji Community near Petroleum-Related Activities

The escalating global concern over air pollution requires rigorous investigations. This study assesses air quality near residential areas affected by petroleum-related activities in Ubeji Community, utilizing Aeroqual handheld mobile multi-gas monitors and air quality multi-meters. Air sampling occurred on three distinct days using multi-gas monitors and meters, covering parameters such as CO, NO2, CH4, NH3, VOCs, Particulate Matter, Temperature, Relative Humidity, and Air Quality Index. Soil and plant samples were collected and analyzed for physicochemical and organic components. Air pollutant concentrations showed significant fluctuations. Carbon monoxide (CO) ranged from 0.00 to 3.22 ppm, NO2 from 0.00 to 0.10 ppm, CH4 from 4.00 to 2083 ppm, NH3 from 371 to 5086 ppm, and VOCs from 414 to 6135 ppm. Soil analysis revealed low total nitrogen, and undetected BTEX levels. Plant samples displayed a pH range of 7.72 to 9.45. CO concentrations, although below WHO limits, indicated potential vehicular and industrial influences. Fluctuations in NO2 and CH4 were linked to traffic, industrial activities, and gas flaring. NH3 levels suggested diverse pollution sources. The result in this study highlights the dynamic nature of air pollution in Ubeji community, emphasizing the urgent need for effective pollution control measures. Although CO concentrations were within limits, continuous monitoring is essential. Elevated NO2 levels gave information on the impact of industrial activities, while high CH4 concentrations may be associated with gas flaring and illegal refining. The study recommends comprehensive measures and collaborative efforts to address these complex issues, safeguarding both the environment and public health. This study shows the potential synergy between air quality sensors and plants for holistic environmental health assessments, offering valuable insights for environmental assessments and remediation endeavours. The findings call for stringent regulations and collaborative efforts to address air pollution in Ubeji community comprehensively.

Investigating the Air Quality Parameters in Louisiana’s Industrial Corridor: A Baton Rouge Case Study

In a local context, sustainable development entails utilizing the current resources—material and immaterial, measurable and immeasurable, popular and unpopular—of the community in a manner that avoids overexploitation and ensures intergenerational equity. This approach prioritizes the safety and health of local citizens, placing communal productivity above corporate profitability. This research aims to assess air quality surrounding 28 chemical industry sites in Baton Rouge, Louisiana, to understand the environmental and health impacts of industrial pollutants, with a focus on environmental justice. Air quality pollutants, including PM2.5, PM10, O3, NO2, CO, and SO2, were monitored for 75 days during the Summer, using the BreezoMeter app. Python, Mapize, and QGIS software technologies were utilized for data analysis and visualization. Findings indicate a reduction in NO2 and CO levels, compared to existing literature. However, the persistent challenge of particulate matter suggests areas for further environmental management efforts. Additionally, the research suggests a significant disparity in air pollution exposure, probably affecting marginalized communities. Although the nature of the study might not fully capture annual pollution trends, the findings highlight the urgent need for the chemical industry to adopt efficient production methods and for policymakers to enhance air quality standards and enforcement, particularly in pollution-sensitive areas. The disproportionate impact of air pollution on vulnerable communities calls for a more inclusive approach to environmental justice, ensuring equitable distribution of clean air benefits and community involvement in pollution management decisions.

Atmospheric Pollutants in a Commercial Region of Fortaleza, Ceará, Brazil: Integration of Health, Environment and Economy in Urban Planning to Improve Air Quality

The accelerated growth of the vehicular fleet, the modernization of large urban centers, and the few adjustments to the road network in Fortaleza have intensified the problems of traffic and emissions of atmospheric pollutants, highlighting the necessity for strategic urban planning initiatives to address the escalating issues of traffic and pollution. With the objective of analyzing the indices of concentrations of atmospheric pollutants and estimating how these levels can affect human health, this work consists of a study of the analysis of air quality in the intense trade region of Fortaleza. For this, the analysis zone was divided into three perimeters (Major - Medium - Minor), where each perimeter was analyzed at 7 am, 12 noon and 5 pm. Concentrations of the type of O3, particulate matter (PM2.5 and PM10), CO2 and HCHO were collected. Our results demonstrate that most of the analyses are within the limits of current legislation;however, at certain times and perimeters, the analyses of CO2 and HCHO exceeded the established limits. In view of the above, we conclude that public policies to control air quality are necessary to reduce the damage to human health and the environment caused by pollutants.

Exploring the Relationship between Spatiotemporal Variations in Air Quality and Meteorological Parameters before and during the COVID-19 Pandemic in Xi’an

The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorological parameters during and before the COVID-19 pandemic. The outcomes of this study indicated that air pollutants, PM2.5, NO2, PM10, CO, and SO2 are likely to decrease during winter (25%, 50%, 30%, 40%, and 35%) to spring (30%, 55%, 38%, 50%, and 40%) and summer (40%, 58%, 60%, 55%, and 47%), respectively. However, the concentration of O3-8h increased by 40%, 55%, and 65% during winter, spring, and summer, respectively. The values of the air quality index decreased during the COVID-19 period. Furthermore, significant positive trends were reported in PM2.5, NO2, PM10, O3, and SO2, and no notable trends in CO during the COVID-19 pandemic. Both during and before the COVID-19 period, PM10, NO2, PM2.5, CO, and SO2 showed a negative correlation with the temperature and a moderately positive significant correlation between O3-8h and temperature. The findings of this study would help understand the air pollution circumstances in Xi’an before and during the COVID-19 period and offer helpful information regarding the implications of different air pollution control strategies.

The Application of Pearson Correlational Analysis Method in Air Quality Analysis of Beijing-Tianjin-Hebei Region

Based on the analysis of monitoring data on six pollution indexes of SO2, NO2, CO, O3, PM10 and PM2.5 from 53 monitoring points in 7 cities, including Beijing, Tianjin, Shijiazhuang, etc., from April 8 of 2014 to July 23 of 2014, this article adopted Pearson correlation coefficient method to determine the relevance among each pollutant of these cities with the help of SPSS. The results showed that such three leading indexes as SO2, PM10 and PM2.5 had strong correlation in Beijing, Tianjin and main cities of Hebei. Finally, some suggestions and preventive measures for the cooperative governance of air pollution in Beijing-Tianjin-Hebei Region were put forward, hoping this can help them.

Investigation and analysis on indoor air quality of large commercial office building in summer

To study the indoor air qualities（IAQ）of large commercial office buildings in Hunan province of China and the corresponding improvement methods,the IAQ of a large commercial office building in Changsha in July,2008,is investigated.A questionnaire survey and field tests are used to collect data.According to the data of twelve rooms in this building,objective evaluation and the subjective evaluation of the IAQ are obtained.Almost all of the environmental parameters in these rooms basically meet the standards of the objective evaluation.But the average concentration of carbon dioxide in most rooms cannot reach the value of the cleanliness standards,1 255 mg/m^3.The average acceptability of the IAQ in these rooms is 71%,which is lower than the value of the ASHRAE 55—1992 standards,80%.The proper increase in the wind speed and the indoor fresh air supply can greatly improve the objective evaluation and the subjective evaluation of the IAQ.

Preliminary Exploration of Indoor Air Quality

Building is an important part of people＇s living. In a certain sense, people are more influenced by indoor, instead of outdoor environment. Actually, IAQ is a kind of demand by people and it is important to create better IAQ to guarantee people＇s health and enhance work efficiency. Multiple methods available to improve IAQ have restrictions of their own and should be integrated. With economic devel- opment, a higher standard of living quality is demanded by people. Therefore, more importance is attached to living environment and indoor air quality has been high- lighted. In the research, dafinition of indoor air quality was introduced, factors influ- encing indoor air quality were analyzed, varieties of room pollutants were described and effective ways to control and improve air quality were proposed, as well.

High-resolution modeling and evaluation of ozone air quality of Osaka using MM5-CMAQ system

High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with complex terrain and land-use. This study uses Community Multiscale Air Quality （CMAQ） model coupled with MM5 mesoscale model for a comprehensive analysis to assess the suitability of such high-resolution modeling system in predicting ozone air quality in the complex terrains of Osaka, Japan. The 1-km and 3-kin grid domains were nested inside a 9-km domain and the domain with 1-km grid covered the Osaka region. High-resolution Grid Point Value-Mesoscale Model （GPV-MSM） data were used after suitable validation. The simulated ozone concentrations were validated and evaluated using statistical metrics using performance criteria set for ozone. Daily maxima of ozone were found better simulated by the 1-krn grid domain than the coarser 9-km and 3-km domains, with the maximum improvement in the mean absolute gross error about 3 ppbv. In addition, 1-km grid results fared better than other grids at most of the observation stations that showed noticeable differences in gross error as well as correlation. These results amply justify the use of the integrated high-resolution MM5-CMAQ modeling system in the highly urbanized region, such as the Osaka region, which has complex terrain and land-use.

Influence of Tropical Cyclones on Hong Kong Air Quality

Tropical cyclones（TCs） constitute one of the major atmospheric activities affecting the air quality of the Pearl River Delta region. In this study, the impact of TCs on air quality in Hong Kong during the TC active season（July–October） from 2000 to 2015 is investigated. It is found that 57.5% of days with concentration of particulate matter with an aerodynamic diameter 10 μm（PM（10）） above the 90th percentile are related to TC activity. TCs in three regions, located to the east, southeast, and southwest of Hong Kong, have obvious impacts on pollutant concentration. When TCs are located east of Hong Kong near Taiwan, 65.5%/38.7% of the days have high or extremely high PM（10）/ozone（O3） levels, which are associated with northerly wind, sinking motion, and relatively low precipitation. When TCs are located southeast of Hong Kong, 48.1%/58.2% of the days have high pollution levels, associated mainly with continental air mass transport. When TCs are south or west of Hong Kong, only 20.8%/16.9% of the days have high PM（10）/O3 levels, and the air quality in Hong Kong is generally good or normal due to TC-associated precipitation, oceanic air mass transport, and an enhanced rising motion. The higher chance of high O3 days when TCs are present between Hong Kong and Taiwan, possibly due to lower-than-normal precipitation along the east coast of China under TC circulation. The results in this study highlight the important influence of TC position and associated atmospheric circulations on the air quality in Hong Kong.

Air quality nearby road traffic tunnel portals: BTEX monitoring

A monitoring campaign of BTEX （benzene, toluene, ethylbenzene, o- m- and p-xylene） was carried out nearby two tunnel portals in the urban area of Naples with the aim to verify air quality in this kind of urban sites. Sampling was carried out using the active adsorption technique. Sampling time was 1 h. Ambient temperature and traffic flow measurements were carried out during each sampling operation. The results indicate that average benzene concentrations at both sites exceed the limit value of 10 μg/Nm^3 established by the European Community （EC） （Dir. 2000/69）. Concentration levels of other BTEX are relatively high as well. A correlation between BTEX concentration and two wheeler vehicle flow was observed.

Global air quality change during the COVID-19 pandemic:Regionally different ozone pollution responses COVID-19

The explosive spread of the 2019 novel coronavirus(COVID-19)provides a unique chance to rethink the relationship between human activity and air pollution.Though related studies have revealed substantial reductions in primary emissions,obvious differences do exist in the responses of secondary pollutants,like ozone(0_(3))pollution.However,the regional disparities of O_(3)responses and their causes have still not been fully investigated.To better elucidate the interrelationship between anthropogenic emissions,chemical production,and meteorological conditions,O_(3)responses caused by lockdowns over different regions were comprehensively explored at a global scale.Observational signals of air-quality change were derived from multi-year surface measurements and satellite retrievals.With similar substantial drops in nitrogen dioxide(NO_(2)),ozone shows rising signals in most areas of both East Asia and Europe,even up to~14 ppb,while a non-negligible declining signal exists in North America,by about 2-4 ppb.Furthermore,the drivers behind the different O_(3)responses are discussed based on meteorological analysis and O_(3)sensitivity diagnosis.On the one hand,O_(3)responses to NO_(2)declines can be affected by the primary dependence on its precursors.On the other hand,it is also highly dependent on meteorological factors,especially temperature.Our study further highlights the great importance of taking into consideration both the regional disparities and synergistic effects of precursor reductions and meteorological influence for scientific mitigation of O_(3)pollution.

A genetic algorithm based stochastic programming model for air quality management

This paper presents a model that can aid planners in defining the total allowable pollutant discharge in the planning region, accounting for the dynamic and stochastic character of meteorological conditions. This is accomplished by integrating Monte Carlo simulation and using genetic algorithm to solve the model. The model is demonstrated by using a realistic air urban scale SO 2 control problem in the Yuxi City of China. To evaluate effectiveness of the model, results of the approach are shown to compare with those of the linear deterministic procedures. This paper also provides a valuable insight into how air quality targets should be made when the air pollutant will not threat the residents' health. Finally, a discussion of the areas for further research are briefly delineated.

Effects of PM2.5 Exposure in Different Air Quality Grades on Daily Outpatient Visits for Childhood Asthma in Shijiazhuang, China

Asthma is a common chronic inflammatory disorder that is more prevalent in children than in adults.China has seen an increasing prevalence of childhood asthma in recentdecades[1].Earlier studies have shown that air particulate matter (PM),particularly fine particulate matter(PM2.5)[2],is an important factor triggering childhood asthma. Since nationalPM2.5data were nota vailabl euntil 2013,

Modeling of air quality with a modified two-dimensional Eulerian model: A case study in the Pearl River Delta (PRD) region of China

A modified two-dimensional Eulerian air quality model was used to simulate both the gaseous and particulate pollutant concentrations during October 21-24, 2004 in the Pearl River Delta （PRD） region, China. The most significant improvement to the model is the added capability to predict the secondary organic aerosols （SOA） concentrations because of the inclusion of the SOA formation chemistry. The meteorological input data were prepared using the CALMET meteorological model. The concentrations of aerosol-bound species such as NO3^-, NH4^＋, SO4^2-, and SOA were calculated in the fine particle size range （〈2.5 μm）. The results of the two-dimensional model were compared to the measurements at the ground level during the PRD Intensive Monitoring Campaign （IMC）. Overall, there were good agreements between the measured and modeled concentrations of inorganic aerosol components and O3. Both the measured and the modeled results indicated that the maximum hourly O3 concentrations exceeded the China National Air Quality Standard. The predicted 24-h average SOA concentrations were in reasonable agreement with those predicted by the method of minimum OC/EC ratio.

Using ADMS models for Air Quality Assessment and Management in China

ADMS-Urban is the most widely used advanced dispersion model for urban areas, being used extensively in China and worldwide, providing a practical tool for assessing and managing urban air quality. In this paper we briefly describe the ADMS dispersion models and give an overview of their use in China. And it describes in more detail the use of ADMS-Urban in Fushun in Liaoning province and in Jinan in Shangdong province respectively, for studies of urban air quality. Finally the conclusions are presented.

Residents’ Willingness to Pay for Improving Air Quality in Jinan, China

Along with the progress of urbanization and environ- mental deterioration, residents’ desire for improved air quality is increasing. In order to quantify an individual’s willingness-to-pay (WTP) for improved air quality in Jinan of eastern China, a contingent valuation method (CVM) was employed. A sample of 1,500 residents was chosen on the basis of multistage sampling methods with face-to-face interviews by using a series of hypo-thetical, open-ended scenario questions which were designed to elicit the respondents’ WTP. Results showed that 59.7% of respondents were able to express their WTP and the mean WTP is 100 Chinese Yuan (CNY) per person per year. A probit model on the probability of a positive WTP and a regression model were developed to find the relationship between endogenous variables and WTP. Most parameters in the econometric analysis had the expected sign. Annual household income and expenditure on treating respiratory diseases significantly influence WTP. The rates of positive WTP and the monetary amount are larger for men than for women. Results also showed that people who lived in more polluted areas were willing to pay more for clean air. Unlike developed countries, clean air may only be considered as a public good in China in that more than 40% of respondents had no incen- tive to bear the costs of attempting to achieve better air quality, which indicates the relatively low environmental consciousness.

A case study of air quality control in Beijing and the surrounding area during the 2015 World Championships and Parade

Based on satellite observations, the effects of emission reduction measures on air pollutants （NO2 （nitrogen dioxide）, SO2 （sulfur dioxide）, and aerosols） were estimated in Beijing and its surroundings during the 2015 World Championships and Parade （WCP） held in Beijing. Compared with the same period in the previous three years （2012-2014）, the tropospheric vertical column densities of NO2 and SO2 in 2015 were significantly reduced in Beijing and its surroundings. During the WCP, aerosol optical depth was reduced most significantly in Beijing, while NO2 and SO2 were reduced most significantly in Hebei and Tianjin, respectively. The meteorological conditions were also favorable during this period. During the WCP, the North China Plain was located under high pressure from the north of China. A southward pressure gradient force and weak northerly and northeasterly winds blocked the transport of pollution from southern and western parts of the industrial area （Hebei, Shanxi and Shandong provinces）. Cold air masses pushed southwards weakly. These conditions were beneficial to the removal of air pollutants in Beijing.