scholarly journals Analysis of Air Pollutant concentration change trend in Urumqi city under the condition of city closed in winter

2021 ◽  
Vol 237 ◽  
pp. 01037
Author(s):  
Haizhen Zhang ◽  
Jiang Wei
Keyword(s):  
Air Pollutant ◽  
Pollutant Concentration ◽  
Atmospheric Environment ◽  
Pollutant Emission ◽  
Energy Control ◽  
Positive Role ◽  
Atmospheric Pollutant ◽  
Epidemic Period ◽  
The City

During the epidemic period, Urumqi has been sealed off from the city’s management, just as “suspended” state.From an environmental point of view, the reduction of energy consumption during the closure of the city can be considered as an energy control to study the resulting reduction of atmospheric pollutant concentration changes.In this paper, the monitoring data of air pollutant concentration in the same period of city closure and normal years are compared, and the results show that the air pollutant concentration has decreased in different degrees during the period of city closure.The largest decrease was44.66% for NO2, -40.13% for CO, -36.44% for PM2.5, and the smallest was-2.06% for SO2.Multivariate analysis of variance showed that energy control had a significant effect on the concentration of pollutants during the city closure, for example NO2 (F=128.96, Sig.=0.000), PM10 (F=29.58, Sig=0.000), PM2.5 (F=13.98, Sig.=0.000), CO(F=46.34;Sig.=0.000). Through the analysis of the data, it can be concluded that the air quality of Urumqi in winter is poor and the concentration of pollutants is high. The energy control during the closing period played a positive role in pollutant emission reduction and effectively improved the quality of atmospheric environment.

scholarly journals Estimation of the spatial distribution of maximum PM10 and PM2.5 concentration in Bandung City and surrounding countries using WRF-Chem Model (case study in July and October 2018)

2021 ◽  
Vol 893 (1) ◽  
pp. 012044
Author(s):  
H Salsabila ◽  
A Turyanti ◽  
DE Nuryanto
Keyword(s):  
Pollutant Dispersion ◽  
Meteorological Factor ◽  
Air Pollutant ◽  
Pollutant Concentration ◽  
Pollutant Emission ◽  
Dispersion Pattern ◽  
Model Case ◽  
The Public ◽  
Pollutant Distribution

Abstract Bandung is one of big cities in Indonesia with high activities on industrial and transportation that will increase the air pollutant emission and causes adversely affect the public health. Based on that matter, monitoring of air pollutant concentration is urgently needed to predict the direction of pollutant dispersion and to analyze which locations are vulnerable to maximum exposure of the pollutant. Field monitoring of air pollutant concentration needs much time and high cost, but modeling could help for this. One of the models that can be used to predict the direction of pollutant distribution is the Weather Research Forecasting/Chemistry (WRF-Chem) model, which is a model that combines meteorological models with air quality models. The output of the WRF-Chem running model on July and October 2018, which has been analyzed visually, showed the dispersion pattern of PM10 and PM2.5 is spread mostly to the west, northwest, and north following the wind direction. According to the output of the WRF-Chem model, Bandung Kulon is the most polluted subdistrict by PM10 and PM2.5 with an exposure frequency of 22 hours (PM10), 24 hours (PM2.5) on July 2018 and 19 Hours (PM10), 14 hours (PM2.5) on October 2018. The correlation value for meteorological parameters is quite high in July 2018 (R = 0.9 for wind speed and R = 0.82 for air temperature). So based on the meteorological factor, WRF-Chem model can be used to predict the direction of pollutant distribution.

scholarly journals On the Unbalanced Atmospheric Environmental Performance of Major Cities in China

2020 ◽  
Vol 12 (13) ◽  
pp. 5391
Author(s):  
Yongrok Choi ◽  
Fan Yang ◽  
Hyoungsuk Lee
Keyword(s):  
Environmental Performance ◽  
Pollution Prevention ◽  
Tax Incentives ◽  
Air Pollutant ◽  
Streaming Data ◽  
Atmospheric Environment ◽  
Pollutant Emission ◽  
Regional Heterogeneity ◽  
Production Scale ◽  
Central Cities

As the largest emitter of CO2, China has also serious air pollution issues. Is it possible to catch these two rabbits under heterogenetic conditions of urbanization? To answer this, this study examines atmospheric environmental performance (SO2, NOx, and PMs) of 30 major cities in China using streaming data from 2011 to 2017. A non-radial SBM-DEA approach is adopted with a meta-frontier model to evaluate regional heterogeneity in atmospheric environmental management. Our results suggest that pollution prevention and regulation policies encouraged synergic development of most cities in the economy and atmospheric environment. On average, atmospheric environmental efficiency of the cities improved from 0.556 to 0.691. However, significantly unbalanced development exists in the regions, requiring customized policies. Eastern cities achieved continuing improvement owing to stringent air pollutant emission policies. Central cities showed a strong improvement but lacked momentum after they achieved certain targets. Western cities lagged behind in the studying period due to both technology gap as well as weak regulation. Furthermore, we identify heterogeneous paths for inefficient cities to enhance their performance using benchmark information. Economically developed eastern cities, such as Beijing, Fuzhou, are facing an over-supply issue. Reshaping their economic structure may be necessary to attain better environmental performance. Central cities face diversified issues. The emphasis of different cities may vary from stringent emission policies to proactive supply-side transition to achieve strong atmospheric management performance. For under-developed cities, preferential policies for investment and tax incentives may be needed to improve their production scale for higher efficiency.

scholarly journals Enhanced atmospheric oxidizing capacity in simulating air quality with updated emission inventories for power plants especially for haze periods over East China

2017 ◽  
Author(s):  
Lei Zhang ◽  
Tianliang Zhao ◽  
Sunling Gong ◽  
Shaofei Kong ◽  
Lili Tang ◽  
...  
Keyword(s):  
Air Quality ◽  
Power Plants ◽  
Emission Inventory ◽  
Environmental Changes ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Atmospheric Environment ◽  
Pollutant Emission ◽  
East China ◽  
Emission Inventories

Abstract. Air pollutant emissions play a determinant role in deteriorating air quality. However, an uncertainty in emission inventories is still the key problem for modeling air pollution. In this study, an updated emission inventory of coal-fired power plants (UEIPP) based on online monitoring data in Jiangsu province of East China for the year of 2012 was implemented in the widely used Multi-resolution Emission Inventory for China (MEIC). By employing the Weather Research and Forecasting Model with Chemistry (WRF-Chem), two simulations were executed to assess the atmospheric environmental change by using the original MEIC emission inventory and the MEIC inventory with the UEIPP. A synthetic analysis shows that (1) compared to the power emissions of MEIC, PM2.5, PM10, SO2 and NOx were lower, and CO, black carbon (BC), organic carbon (OC) and NMVOCs were higher in the UEIPP, reflecting a large discrepancy in the power emissions over East China; (2) In accordance with the changes of UEIPP, the modeled concentrations were reduced for SO2 and NO2, and increased for most areas of primary OC, BC and CO, whose concentrations in atmosphere are highly dependent on emission changes. (3) Interestingly, when the UEIPP was used, the atmospheric oxidizing capacity significantly reinforced, reflecting by increased oxidizing agents, e.g. O3 and OH, thus directly strengthened the chemical production from SO2 and NOx to sulfate and nitrate, which offset the reduction of primary PM2.5 emissions especially in the haze days. This study indicated the importance of updating air pollutant emission inventories in simulating the complex atmospheric environment changes with the implications on air quality and environmental changes.

Simulation of Air Quality and Pollution Control Countermeasures of Chengdu Urban Agglomeration

2012 ◽  
Vol 610-613 ◽  
pp. 1387-1397 ◽  
Author(s):  
Wen Yong Wang ◽  
Nan Chen ◽  
Xiao Juan Ma
Keyword(s):  
Air Quality ◽  
Sulfur Dioxide ◽  
Pollution Sources ◽  
Air Pollutant ◽  
Urban Agglomeration ◽  
Pollutant Concentration ◽  
Pollutant Emission ◽  
Air Quality Model ◽  
Quality Model ◽  
Allowable Limit

The CMAQ model (Community Multiscale Air Quality model) was used to stimulate the atmospheric environmental quality of Chengdu urban agglomeration. The result shows that air pollutant concentration in some zones of the urban agglomeration is higher than the allowable limit of the national grade II standard. Fortunately, such zones only cover a small area. Zones where the average daily and annual PM10 concentration is higher than the allowable limit only account for 4% of the total area of Chengdu urban agglomeration. Less than 1% of the total area has the concentration of other pollutants higher than the limit. Zones with pollutant concentration higher than the limit are mainly distributed in Chengdu City, Mianyang City, and Meishan City. Pollutants emitted from the cities of Chengdu urban agglomeration shift on to and interact with each other. Therefore, the air pollutant concentration of one city is partially attributable to pollutants emitted from its own pollution sources and a part of or even most of it results from pollutants from other cities. For example, regarding PM10 in air of Deyang City, only 12% comes from its own pollution sources, and 55% comes from pollution sources of Chengdu, and the rest 29% comes from pollution sources of Mianyang. Regarding Sulfur dioxide in air of Chengdu, 59% comes from local pollution sources of Chengdu and 23% comes from pollution sources of Deyang. Other pollutants are also subject to such a rule. As in the urban agglomeration, there are zones where pollutant concentration is higher than the allowable limit, the existing pollution sources must be further controlled by setting reduction target according to the total capacity. The pollutant emission should be reduced by means of eliminating backward productivity, adjusting structure and layout of industries, and controlling pollution sources in depth to effectively improve the regional environmental air quality. At the same time, as pollutants emitted from the cities interact with each other, the 5 cities must sign a joint prevention and control agreement to collaborate in control of sulfur dioxide, nitrogen oxides, smoke and dust, and organic pollutants.

scholarly journals Improving the Professional Level of Managers Through Individualized Recommendation to Enhance the Quality of Air Pollutant Management in China

2019 ◽  
Vol 11 (21) ◽  
pp. 6094
Author(s):  
Xiao ◽  
Qin ◽  
Fu ◽  
Zhang
Keyword(s):  
Air Pollutants ◽  
Recommendation System ◽  
Fossil Fuel ◽  
Rapid Development ◽  
Air Pollutant ◽  
Pollutant Emission ◽  
Full Picture ◽  
Regional Air Quality ◽  
Assessment Strategies

With the rapid development of the economy, and fossil fuel consumption lacking systematic emission controls, China has experienced substantially elevated concentrations of air pollutants, which not only degrades regional air quality but also poses significant impacts on public health. However, faced with the demand for a large number of experts in air pollution protection, people with real expertise for air pollutant management are difficult to find. Therefore, individualized recommendation is an effective and sustainable method for enhancing the professional level of managers and is good for improving the quality of air pollutant management. Thus, this paper initially proposes a novel framework to recommend strengths in air pollutant management. This framework comprises four stages: data preprocessing is the first stage; then, after constructing ability classifications and ability assessment strategies, activity experiences are transformed into corresponding ability values; next, a multilayer perceptron deep neural network (MLP-DNN) is used to predict potential types according to their ability values; finally, a hybrid system is constructed to recommend suitable and sustainable potential managers for air pollutant management. The experiments indicate that the proposed method can assess the full picture of people’s strengths, which can recommend suggestions for building a scientific and rational specialties recommendation system for governments and schools. This method can have significant effects on pollutant emission reduction by enhancing the professional level of managers with regard to air pollutant management.

scholarly journals Air Pollutant Concentration Forecasting Using Long Short-Term Memory Based on Wavelet Transform and Information Gain: A Case Study of Beijing

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Bingchun Liu ◽  
Xiaoling Guo ◽  
Mingzhao Lai ◽  
Qingshan Wang
Keyword(s):  
Prediction Model ◽  
Wavelet Decomposition ◽  
Information Gain ◽  
Air Pollutant ◽  
Pollutant Concentration ◽  
High Dimensional ◽  
Concentration Data ◽  
Atmospheric Pollutant ◽  
Data Set ◽  
Concentration Prediction

Air pollutant concentration forecasting is an effective way which protects health of the public by the warning of the harmful air contaminants. In this study, a hybrid prediction model has been established by using information gain, wavelet decomposition transform technique, and LSTM neural network, and applied to the daily concentration prediction of atmospheric pollutants (PM2.5, PM10, SO2, NO2, O3, and CO) in Beijing. First, the collected raw data are selected by feature selection by information gain, and a set of factors having a strong correlation with the prediction is obtained. Then, the historical time series of the daily air pollutant concentration is decomposed into different frequencies by using a wavelet decomposition transform and recombined into a high-dimensional training data set. Finally, the LSTM prediction model is trained with high-dimensional data sets, and the parameters are adjusted by repeated tests to obtain the optimal prediction model. The data used in this study were derived from six air pollution concentration data in Beijing from 1/1/2014 to 31/12/2016, and the atmospheric pollutant concentration data of Beijing between 1/1/2017 and 31/12/2017 were used to test the predictive ability of the data set test model. The results show that the evaluation index MAPE of the model prediction is 7.45%. Therefore, the hybrid prediction model has a higher value of application for atmospheric pollutant concentration prediction, because this model has higher prediction accuracy and stability for future air pollutant concentration prediction.

scholarly journals OLYMPUS v1.0: Development of an integrated air pollutant and GHG urban emissions model – Methodology and calibration over the greater Paris

2018 ◽  
Author(s):  
Arthur Elessa Etuman ◽  
Isabelle Coll
Keyword(s):  
Air Pollutants ◽  
Travel Demand ◽  
Road Traffic ◽  
Air Pollutant ◽  
Atmospheric Environment ◽  
Health Economy ◽  
Unit Energy ◽  
European Environmental Agency ◽  
The Impact ◽  
The City

Abstract. Air pollutants and greenhouse gases have many effects on health, economy, urban climate and atmospheric environment. At the city level, the transport and heating sectors contribute significantly to air pollution. In order to quantify the impact of urban policies on anthropogenic air pollutants, the main processes leading to emissions need to be understood: they mainly include mobility for work and leisure and household behavior, themselves impacted by a variety of social parameters. In this context, the Olympus modeling platform has been designed for environmental decision support. It generates a synthetic population of individuals and defines the mobility of each individual in the city through an activity-based approach of the travel demand. The model then spatializes road traffic taking into account congestion on the road network. It also includes a module that estimates the energy demand of the territory by calculating the unit energy consumption of households and the tertiary sector. Finally, the emissions associated with all the modeled activities are calculated using the COPERT emission factors for the traffic, and the European Environmental Agency (EEA) methodology for heating-related combustions. The comparison of emissions with AIRPARIF's regional inventory shows discrepancies that are consistent with differences in assumptions and input data, mainly in the sense of underestimation. The methodological choices, as well as the potential ways of improvement, including the refinement of traffic congestion modeling and of the transport of goods, are discussed.

scholarly journals EVOLUTION OF POLLUTANTS EMISSIONIN RELATION TOROAD TRAFFIC IN THE CITY OF LOME (TOGO) FROM 2010 TO 2019

2021 ◽  
Vol 9 (12) ◽  
pp. 51-57
Author(s):  
Kokou SABI ◽  
◽  
Hezouwe SONLA ◽  
Moursalou KORIKO ◽  
Kokou Eric GBEDJANGNI ◽  
...  
Keyword(s):  
Air Pollutants ◽  
Emission Inventory ◽  
Road Traffic ◽  
Petroleum Products ◽  
Air Pollutant ◽  
Capital City ◽  
Pollutant Emission ◽  
Volatile Organic ◽  
Pollutants Emission ◽  
The City

The automobile fleet in Togo has increased in the last decades with a patchwork of vehicles that are in majority older than ten (10) years. Until 2019, the car fleet in Togo was almost dependent upon petroleum products, and was consequentlya source of air pollutants emission. Lome is the capital city of Togo with the characteristic of having the highest road traffic volume that significantly impacts air quality. In accordance with the EMEP/EEA air pollutant emission inventory guide and the COPERT method, emissions of carbone monoxide (CO), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOCs) and particulate matter (PM) are respectively estimated to: 2621.674 tCO 82.444 tNOx 558.778 tNMVOC and 7.241 tPM. In the time series 2010-2019, emissions of CO, NMVOCs and NOx fell overall with average yearly rates by respectively 83,0234 66,4888 and 0,8073 t/year whereas the PM emission rose(0,8208 t/year).

scholarly journals OLYMPUS v1.0: development of an integrated air pollutant and GHG urban emissions model – methodology and calibration over greater Paris

2018 ◽  
Vol 11 (12) ◽  
pp. 5085-5111 ◽  
Author(s):  
Arthur Elessa Etuman ◽  
Isabelle Coll
Keyword(s):  
Air Pollutants ◽  
Energy Demand ◽  
Travel Demand ◽  
Road Traffic ◽  
Air Pollutant ◽  
Atmospheric Environment ◽  
Unit Energy ◽  
European Environmental Agency ◽  
The Impact ◽  
The City

Abstract. Air pollutants and greenhouse gases have many effects on health, the economy, urban climate and atmospheric environment. At the city level, the transport and heating sectors contribute significantly to air pollution. In order to quantify the impact of urban policies on anthropogenic air pollutants, the main processes leading to emissions need to be understood: they principally include mobility for work and leisure as well as household behavior, themselves impacted by a variety of social parameters. In this context, the OLYMPUS modeling platform has been designed for environmental decision support. It generates a synthetic population of individuals and defines the mobility of each individual in the city through an activity-based approach of travel demand. The model then spatializes road traffic by taking into account congestion on the road network. It also includes a module that estimates the energy demand of the territory by calculating the unit energy consumption of households and the commercial–institutional sector. Finally, the emissions associated with all the modeled activities are calculated using the COPERT emission factors for traffic and the European Environmental Agency (EEA) methodology for heating-related combustion. The comparison of emissions with AIRPARIF's regional inventory shows discrepancies that are consistent with differences in assumptions and input data, mainly in the sense of underestimation. The methodological choices and the potential ways of improvement, including the refinement of traffic congestion modeling and of the transport of goods, are discussed.

Model Pemberdayaan Usaha Mikro Dan Pengaruhnya Terhadap Kemandirian Usaha

2015 ◽  
Vol 2 (1) ◽  
pp. 75-93
Author(s):  
Mudasetia Hamid ◽  
Evy Rosalina Widyayanti
Keyword(s):  
Human Resources ◽  
Small And Medium Enterprises ◽  
Poverty Rate ◽  
Cultural Centers ◽  
Central Java ◽  
Tourism Education ◽  
The Indian Ocean ◽  
Medium Enterprises ◽  
The City

Yogyakarta is a city and the capital of Yogyakarta Special Region in Java, Indonesia. It is renowned as a center of tourism, education and culture. Yogyakarta is one of the foremost cultural centers of Java. This region is located at the foot of the active merapi vulcano. Yogyakarta is often called the main gateway to the Central Java as where it is geographically located. It stretches from Mount Merapi to the Indian Ocean. This province is one of the most densely populated areas of Indonesia. Yogyakarta is popular tourist destination in indonesia after Bali. These have attracted large number of visitors from across Indonesia and abroad to the city. This status makes Yogyakarta is one of the most heterogeneus cities in Indonesia. In edition, Yogyakarta has attracted large number of people to reside in this city for business. One of these comers is small entrepreneurs with their market munchies enterprise (specially a traditional snack trader). This business is one of famous business in Yogyakarta, we will find rows of pavement vendors selling market munchies. The students and tourists are their main target customers. Market munchies enterprise is part of small and medium enterprises SMEs as livelihood activities. SMEs has an important role in economic growth of Indonesia. Therefore, it is very important to develop and strengthen the micro enterprise empowerment. Micro enterprise empowerment is one of strategy to reduce the poverty rate in Indonesia. Major challenger in implement this program are that micro entrepreneurs are conventional and have satisfied with their revenue. It is very important to develop a comprehensive and sustainable micro enterprise empowerment which consist of strengthen the quality of human resources, maximize the government’s roles, empower the enterprise capital and strengthen the partnership and autonomous. Micro enterprise autonomy will contribute to the economic and investment climate. This will lead to establish an accountable enterprise both for the micro enterprise and customers which at the end will strengthen the development of the micro enterprise in Yogyakarta.Keyword: micro entreprise, human resources, government roles, capital, partnership and autonomous.

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