BIG DATA TECHNOLOGY FRAMEWORK
AND DATA UTILIZATION FOR URBAN
ENVIRONMENTAL POLLUTION
MANAGEMENT
Nan Li*
School of Marxism, Capital Normal University, Beijing, 100089, China.
linanxa@126.com
Zheng Ma
Foshan Electric Construction Group Limited, Foshan, Guangdong, 528000, China.
Reception: 06/04/2023 Acceptance: 30/05/2023 Publication: 26/06/2023
Suggested citation:
Li, N. and Ma, Z. (2023). Big data technology framework and data
utilization for urban environmental pollution management. 3C Tecnología.
Glosas de innovación aplicada a la pyme, 12(2), 204-218. https://doi.org/
10.17993/3ctecno.2023.v12n2e44.204-218
https://doi.org/10.17993/3ctecno.2023.v12n2e44.204-218
3C Tecnología. Glosas de innovación aplicadas a la pyme. ISSN: 2254-4143
Ed.44 | Iss.12 | N.2 April - June 2023
204
BIG DATA TECHNOLOGY FRAMEWORK
AND DATA UTILIZATION FOR URBAN
ENVIRONMENTAL POLLUTION
MANAGEMENT
Nan Li*
School of Marxism, Capital Normal University, Beijing, 100089, China.
linanxa@126.com
Zheng Ma
Foshan Electric Construction Group Limited, Foshan, Guangdong, 528000, China.
Reception: 06/04/2023 Acceptance: 30/05/2023 Publication: 26/06/2023
Suggested citation:
Li, N. and Ma, Z. (2023). Big data technology framework and data
utilization for urban environmental pollution management. 3C Tecnología.
Glosas de innovación aplicada a la pyme, 12(2), 204-218. https://doi.org/
10.17993/3ctecno.2023.v12n2e44.204-218
https://doi.org/10.17993/3ctecno.2023.v12n2e44.204-218
ABSTRACT
Urban environmental pollution management is of great practical significance to
achieving sustainable urban economic development. To improve the efficiency of
urban environmental pollution management, we have established a big data
technology framework for urban environmental pollution treatment. The relevant
pollution data collected are used for targeted pollution treatment. The results show
that the average efficiency of environmental pollution control in the whole province of
China has increased from 33.67% to 63.67%, an increase of 46%. Among them, the
efficiency of environmental pollution control in Guangdong has increased most
significantly, with a relative position of 26.47%, which is at the top of the list. Inner
Mongolia has the weakest increase in environmental pollution control efficiency, with
an appreciation of 6.89% relative to its position, while the other 16 provinces and
cities have little change in environmental pollution control efficiency. between 2010
and 2020, the urban pollution and environmental treatment costs that residents need
to bear changed significantly, with fluctuations of around 30%.
KEYWORDS
Environmental pollution; pollution management; big data; pollution management
efficiency; economic analysis
INDEX
ABSTRACT
KEYWORDS
1. INTRODUCTION
2. CONSTRUCTION OF AN EVALUATION PLATFORM FOR URBAN
ENVIRONMENTAL POLLUTION MANAGEMENT BASED ON BIG DATA
2.1. Basic concepts of big data
2.2. Technical Framework
2.3. Research Program
2.4. Environmental pollution big data processing process
3. TECHNICAL EFFICIENCY OF URBAN ENVIRONMENTAL POLLUTION
MANAGEMENT
4. ANALYSIS AND DISCUSSION
4.1. Overall environmental pollution control efficiency performance
4.2. Performance of environmental pollution control efficiency by provinces and
cities
4.3. Economic Analysis of urban pollution environmental management
5. CONCLUSION
REFERENCES
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1. INTRODUCTION
Environmental pollution control is an important initiative to promote the construction
of ecological civilization [1, 2]. For ordinary people, a high-quality living environment
with blue skies and white clouds is the basic condition for building an ecological
civilization of beautiful China and realizing the Chinese dream of rejuvenation of the
Chinese nation [3]. In building an ecological civilization society, comprehensive
prevention and control of air pollution should be solidly promoted [4, 5]. Further
significant reduction of heavily polluted weather and gradual improvement of air
quality [6]. Environmental pollution control is a powerful grip to create an upgraded
version of China's economy [7, 8]. At present, China's crude development mode of
high input, high consumption, high pollution, and low efficiency has not been
fundamentally transformed, which is the fundamental cause of serious pollution [9]. In
recent decades, China's economy has been developing steadily and rapidly. China
has made remarkable achievements in economic construction in the world [10], but
along with the economic development, China has paid a huge environmental cost.
Along with China's rapid economic growth, China's ecological environment is
deteriorating and pollution problems are becoming increasingly serious. The pollution
problem has now become a major challenge to China's sustainable economic
development [11, 12]. In China, with the advancement of urbanization, more and more
people are living in cities. The corresponding urban environmental pollution has
become an important part of China's environmental pollution, so it is of epochal
significance to do a good job in urban environmental pollution management to build a
beautiful China and promote China's modern economic construction.
In China, ecological and environmental problems brought about by urbanization are
gradually emerging [13]. Therefore, the issue of urban environmental pollution
management has received great attention, and people are eager to solve a series of
environmental pollution problems such as water shortage and pollution, and rapid
reduction of air quality [14]. People are eager to aspire to and pursue a healthy, green,
and sustainable ecological living environment. Faced with the current rapid population
growth, excessive consumption of resources, and serious environmental pollution, the
sustainable development path is the inevitable way of development nowadays [15-22].
At present, for urban environmental pollution management, there are still problems
such as small investment in environmental protection, insufficient urban environmental
infrastructure construction, and insufficient policies and laws and regulations for
environmental protection [23, 24]. In urban environmental pollution management, the
lack of environmental protection investment has led to weak comprehensive urban
pollution management capacity. Further, the slow pace of urban environmental
infrastructure construction, urban domestic waste, hazardous waste treatment
capacity, etc. is not able to keep up with the pace of urban development, thus leading
to serious pollution problems over time.
In terms of urban environmental pollution management, urban environmental
pollution management is closely related to people's lives [25]. Therefore, prevention
and treatment of urban environmental pollution management has received wide
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1. INTRODUCTION
Environmental pollution control is an important initiative to promote the construction
of ecological civilization [1, 2]. For ordinary people, a high-quality living environment
with blue skies and white clouds is the basic condition for building an ecological
civilization of beautiful China and realizing the Chinese dream of rejuvenation of the
Chinese nation [3]. In building an ecological civilization society, comprehensive
prevention and control of air pollution should be solidly promoted [4, 5]. Further
significant reduction of heavily polluted weather and gradual improvement of air
quality [6]. Environmental pollution control is a powerful grip to create an upgraded
version of China's economy [7, 8]. At present, China's crude development mode of
high input, high consumption, high pollution, and low efficiency has not been
fundamentally transformed, which is the fundamental cause of serious pollution [9]. In
recent decades, China's economy has been developing steadily and rapidly. China
has made remarkable achievements in economic construction in the world [10], but
along with the economic development, China has paid a huge environmental cost.
Along with China's rapid economic growth, China's ecological environment is
deteriorating and pollution problems are becoming increasingly serious. The pollution
problem has now become a major challenge to China's sustainable economic
development [11, 12]. In China, with the advancement of urbanization, more and more
people are living in cities. The corresponding urban environmental pollution has
become an important part of China's environmental pollution, so it is of epochal
significance to do a good job in urban environmental pollution management to build a
beautiful China and promote China's modern economic construction.
In China, ecological and environmental problems brought about by urbanization are
gradually emerging [13]. Therefore, the issue of urban environmental pollution
management has received great attention, and people are eager to solve a series of
environmental pollution problems such as water shortage and pollution, and rapid
reduction of air quality [14]. People are eager to aspire to and pursue a healthy, green,
and sustainable ecological living environment. Faced with the current rapid population
growth, excessive consumption of resources, and serious environmental pollution, the
sustainable development path is the inevitable way of development nowadays [15-22].
At present, for urban environmental pollution management, there are still problems
such as small investment in environmental protection, insufficient urban environmental
infrastructure construction, and insufficient policies and laws and regulations for
environmental protection [23, 24]. In urban environmental pollution management, the
lack of environmental protection investment has led to weak comprehensive urban
pollution management capacity. Further, the slow pace of urban environmental
infrastructure construction, urban domestic waste, hazardous waste treatment
capacity, etc. is not able to keep up with the pace of urban development, thus leading
to serious pollution problems over time.
In terms of urban environmental pollution management, urban environmental
pollution management is closely related to people's lives [25]. Therefore, prevention
and treatment of urban environmental pollution management has received wide
https://doi.org/10.17993/3ctecno.2023.v12n2e44.204-218
attention. Zhang, X [26] surveyed the environmental concentration and change
characteristics of ozone and its precursors in Beijing from May-June 2014-2017 to
study heavy ozone pollution. Their study showed the need to adjust control measures
according to the changes in ozone precursors and strengthen the coordinated control
of urban environmental pollution prevention and control in long-term planning. Fei, F
[27] considered municipal biological waste as an organic part of municipal solid waste
and a major waste type in low- and middle-income countries. They used the concept
of industrial ecology to conduct a complete planning exercise for urban bio-waste
disposal systems. Their study showed that conducting urban environmental pollution
management has significant economic, environmental, and social benefits. In a study
by Guo, J.X [28], they studied showed that in large cities, the coordinated
development of pollutants and carbon reduction in the transportation sector can help
to achieve urban pollution prevention and carbon reduction. They proposed a bottom-
up mathematical model of vehicle development for multiple periods, analyzing the air
pollution emission paths and energy restructuring paths, as well as the synergistic
benefits of CO2 emission reduction. Further, Zhao, B [29] argued that spatially explicit
urban air quality information is important for developing effective air quality control
measures. They did this by collecting real-time spatially resolved data on fine
particulate matter concentrations. A decision tree model was developed to infer the
distribution of PM2.5 concentrations. Tang, W [30] considered water pollution as the
main environmental problem among urban environmental pollution. They analyzed
various long-term water quality, wastewater treatment plants, and pollutant discharge
data to systematically understand the process of water pollution control in China over
the past two decades. They suggested that wastewater collection and treatment
capacity should be further improved to address the gap between effluent discharge
limits of wastewater treatment plants and environmental quality standards for surface
water. Xiong, W [31] proposed wastewater recycling as the most effective strategy to
reduce the impact of urban water ecosystems. Wang, R [32] in their study pointed out
that polluted urban river systems may be an important source of atmospheric methane
and nitrous oxide sources. Xiao, Q [33] suggested that environmental investments
could reduce the partial pressure of CO2 in small eutrophic urban lakes. Their results
show that anthropogenic activities strongly influence the dynamic distribution of lake
CO2 and that environmental investments, such as ecological restoration and
reduction of nutrient discharges, can significantly reduce CO2 emissions from inland
lakes. In all the above studies, we can find that for urban environmental pollution
prevention and control, mainly includes several aspects such as air pollution, water
pollution, and pollution emission. In conducting urban pollution prevention and control,
previous studies tend to focus on one direction to carry out. However, urban
environmental pollution treatment is a comprehensive system that needs to be carried
out in several aspects such as air pollution, water pollution, and pollution discharge.
Urban environmental pollution management is of great practical significance to
achieve sustainable development of the urban economy. In urban environmental
pollution management, it involves several aspects such as air pollution, water
pollution, and pollution discharge. Therefore, when pollution prevention and control is
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carried out, a large amount of data on the generation of pollutants and the treatment
of pollutants will be generated. Therefore, in urban pollution control, we need to
analyze a large amount of data to determine the areas that need to be dealt with in
urban pollution control. In this research work, we establish a big data technology
framework for urban environmental pollution treatment. Through the collected
pollution data for pollution prevention and treatment, then improve the efficiency of
urban environmental pollution treatment.
2. CONSTRUCTION OF AN EVALUATION PLATFORM
FOR URBAN ENVIRONMENTAL POLLUTION
MANAGEMENT BASED ON BIG DATA
As urban environmental pollution problems become increasingly serious, a large
amount of real environmental pollution data are collected and made public by
government agencies [34, 35]. Big data technology is used to automatically extract
important pollution causes from these environmental pollution big data and establish a
big data-based urban environmental pollution management evaluation platform to
better solve a series of problems in urban environmental pollution management in
China. In environmental pollution big data, a large amount of environmental pollution
data covers the detailed records of environmental pollution generated within the city.
Specifically, by using frontier technologies of information science such as big data and
artificial intelligence, we can propose to solve the drawbacks of monolithic urban
environmental pollution governance and improve the quality and efficiency of urban
environmental governance.
2.1. BASIC CONCEPTS OF BIG DATA
Big Data on environmental pollution is different from the traditional data
management model in that it brings radical changes in the way data is collected, data
pre-processing (stream processing vs. batch processing), and data algorithm
approach. At present, we have experienced the evolution of the operational phase,
user original phase, and perceptual system phase. This is mainly reflected in the
following aspects.
1.
Data scale. Due to the booming development of urban informatization,
emerging services such as the Internet of Things can collect unprecedented
data types as well as data quantities.
2. Processing tools. At this stage, there are 4 paradigms, based on the new data
thinking approach of environmental pollution big data collection for processing
various research objects as well as various heterogeneous data. The above 4
paradigms are introduced as shown in Table 1.
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carried out, a large amount of data on the generation of pollutants and the treatment
of pollutants will be generated. Therefore, in urban pollution control, we need to
analyze a large amount of data to determine the areas that need to be dealt with in
urban pollution control. In this research work, we establish a big data technology
framework for urban environmental pollution treatment. Through the collected
pollution data for pollution prevention and treatment, then improve the efficiency of
urban environmental pollution treatment.
2. CONSTRUCTION OF AN EVALUATION PLATFORM
FOR URBAN ENVIRONMENTAL POLLUTION
MANAGEMENT BASED ON BIG DATA
As urban environmental pollution problems become increasingly serious, a large
amount of real environmental pollution data are collected and made public by
government agencies [34, 35]. Big data technology is used to automatically extract
important pollution causes from these environmental pollution big data and establish a
big data-based urban environmental pollution management evaluation platform to
better solve a series of problems in urban environmental pollution management in
China. In environmental pollution big data, a large amount of environmental pollution
data covers the detailed records of environmental pollution generated within the city.
Specifically, by using frontier technologies of information science such as big data and
artificial intelligence, we can propose to solve the drawbacks of monolithic urban
environmental pollution governance and improve the quality and efficiency of urban
environmental governance.
2.1. BASIC CONCEPTS OF BIG DATA
Big Data on environmental pollution is different from the traditional data
management model in that it brings radical changes in the way data is collected, data
pre-processing (stream processing vs. batch processing), and data algorithm
approach. At present, we have experienced the evolution of the operational phase,
user original phase, and perceptual system phase. This is mainly reflected in the
following aspects.
1. Data scale. Due to the booming development of urban informatization,
emerging services such as the Internet of Things can collect unprecedented
data types as well as data quantities.
2. Processing tools. At this stage, there are 4 paradigms, based on the new data
thinking approach of environmental pollution big data collection for processing
various research objects as well as various heterogeneous data. The above 4
paradigms are introduced as shown in Table 1.
https://doi.org/10.17993/3ctecno.2023.v12n2e44.204-218
Table 1. Comparison of big data processing paradigms
3.
Data types. Traditional data management models have a single type of data
while emerging services such as IoT can capture a wide variety of big data
types (structured, semi-structured, and unstructured). Of these, the latter two
data types account for the largest share.
2.2. TECHNICAL FRAMEWORK
This paper constructs a big data-based urban environmental pollution management
evaluation platform including three parts: environmental pollution big data access
layer, environmental pollution big data processing layer, and environmental pollution
big data application layer, as shown in Figure 1. In the environmental pollution big
data access layer, for the problems of diverse sources and different structures of
factory emission information system data within the city, Spark distributed is used to
pre-process the environmental pollution big data, and the quality and reliability of the
environmental pollution big data are ensured by integrating and classifying the
environmental pollution big data. In the environmental pollution big data processing
layer, the big data-based urban environmental pollution governance evaluation
platform constructs a series of environmental pollution big data engines by selecting
appropriate environmental pollution big data analysis technologies to conduct efficient
and in-depth data mining and fusion analysis of environmental pollution big data. At
the application layer of environmental pollution big data, the big data-based urban
environmental pollution governance evaluation platform transforms the problem of
excessive emissions of factory enterprises into a big data analysis problem by
transforming them into a big data analysis problem. The evaluation model of urban
environmental pollution management, such as establishing effective pollutant
treatment measures and finding low-cost solutions, realizes sustainable development
of the urban economy and environment, etc.
Scientific Paradigm Methodology
Empirical Description of natural phenomena
Theoretical Use of models, generalization
Computational Simulation of complex phenomena
Data Exploration
Instrument-captured or simulator-generated data; software
processing; computer-stored information; scientists analyzing
databases
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Figure 1. The framework of urban environmental pollution management evaluation platform
based on big data.
2.3. RESEARCH PROGRAM
This paper proposes a big data-based urban environmental pollution management
evaluation platform that enables a customizable implementation approach based on
the environmental governance needs of Chinese cities. We investigated exhaustive
projects of environmental governance across China, summarized common problems
prevalent in intra-city factory emissions, developed specific research solutions for
these problems, and finally validated and analyzed the research content using the
environmental pollution big data from the above-mentioned research.
It is worth mentioning that the big data's urban environmental pollution
management evaluation platform flags the waste emissions of each factory in the city.
We extract irregular waste emission events from environmental pollution big data and
automatically build a risk assessment model of environmental pollution damage from
relevant waste based on the waste composition, emission cycle, and total emission of
the factory. Improve laws and regulations to clarify the obligations of the public and
enterprises in participating in urban environmental pollution control, and the
government to promote green and low-carbon consumption concepts. Eliminate the
backward production equipment as well as improve the production process of urban
factories, increase pollution control, and complete the task of pollution reduction. To
provide a strong solution for urban environmental pollution management.
2.4. ENVIRONMENTAL POLLUTION BIG DATA
PROCESSING PROCESS
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Figure 1. The framework of urban environmental pollution management evaluation platform
based on big data.
2.3. RESEARCH PROGRAM
This paper proposes a big data-based urban environmental pollution management
evaluation platform that enables a customizable implementation approach based on
the environmental governance needs of Chinese cities. We investigated exhaustive
projects of environmental governance across China, summarized common problems
prevalent in intra-city factory emissions, developed specific research solutions for
these problems, and finally validated and analyzed the research content using the
environmental pollution big data from the above-mentioned research.
It is worth mentioning that the big data's urban environmental pollution
management evaluation platform flags the waste emissions of each factory in the city.
We extract irregular waste emission events from environmental pollution big data and
automatically build a risk assessment model of environmental pollution damage from
relevant waste based on the waste composition, emission cycle, and total emission of
the factory. Improve laws and regulations to clarify the obligations of the public and
enterprises in participating in urban environmental pollution control, and the
government to promote green and low-carbon consumption concepts. Eliminate the
backward production equipment as well as improve the production process of urban
factories, increase pollution control, and complete the task of pollution reduction. To
provide a strong solution for urban environmental pollution management.
2.4. ENVIRONMENTAL POLLUTION BIG DATA
PROCESSING PROCESS
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The data sources of environmental pollution big data are widely available, and the
application requirements and data types are different, but the most basic processing
process is consistent, as shown in Figure 2 Basic processing process of big data. The
entire processing process of environmental pollution big data can be defined as the
extraction and integration of a wide range of heterogeneous data sources with the
assistance of suitable tools, and the results are stored uniformly according to certain
standards. The stored environmental pollution big data is analyzed using appropriate
data analysis techniques, and the relevant environmental pollution factors are
extracted from the environmental pollution big data and the results are fed back to
government agencies in an appropriate way so that they can enact policies and take
action for pollution control.
Figure 2. Basic processing flow of big data
3. TECHNICAL EFFICIENCY OF URBAN
ENVIRONMENTAL POLLUTION MANAGEMENT
This paper evaluates the technical efficiency of urban environmental pollution
control based on data envelopment analysis (DEA). DEA solves the optimal
production frontier surface through linear programming and compares the production
possibilities of each multi-input and multi-output similar decision-making unit (DMU)
with the previous optimal frontier surface to obtain a measure of the relative efficiency
of each DMU. The specific evaluation criteria process is as follows.
(1)
(2)
Where, is the input; is the output; is the weight; , and denote the
number of input variables, output variables and DMUs, respectively; is the technical
Extraction conversion
integration
Lock target
data
Data mining
Structure
OLAF
Evaluation
and detection
Visual design
Fi(y,x∣C,S) = min {λ:λx∈L(y∣C,S)}
s
⋅t⋅L(y∣C,S) =
{
(x1,x2, …xN):
K
∑
k=1
Zkykm ⩾ym,
K
∑
i=1
zixin ⩽θkxkn,
K
∑
k=1
zkxkn ⩽xn
}
x
y
z
N
M
K
Fi
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efficiency of the ith DMU; is the total number of different types of big data; is the
total number of big data samples. In addition, 34 provincial regions in China are
selected as DMUs in this paper, and the period for analysis is from 2010 to 2020. To
store, manage and analyze environmental pollution big data, we use Spark distributed
computing framework for technical implementation. This paper based on Spark
distributed computing can reduce the overhead caused by data movement and
transparently provide high reliability and high-performance computing for upper-layer
applications
4. ANALYSIS AND DISCUSSION
4.1. OVERALL ENVIRONMENTAL POLLUTION CONTROL
EFFICIENCY PERFORMANCE
To realize the sustainable development of the urban ecological environment, we
introduce big data technology, which should firstly collect the urban ecological
environment data according to the urban environmental pollution situation and the
governance needs, and build the corresponding standard system structure according
to the results obtained from the collection. Finally, pollution treatment should be
completed in strict accordance with the corresponding standard indicators. The
average efficiency scores of environmental pollution control for the whole province of
China, eastern China, central China, and Western China are compiled in Figure 3,
which shows that in the early 21st century, the efficiency of environmental pollution
control in all regions of China was below 50%. With the proposed policies of energy
conservation and emission reduction, carbon peaking, and carbon neutrality in China,
the efficiency of environmental pollution management gradually began to improve
across China. Between 2010 and 2020, the average efficiency score for
environmental pollution control across China's provinces increased from 33.67% to
63.67%, an improvement of 46%. Overall, the efficiency of environmental pollution
control across China is increasing, thanks to strong government support for
environmental protection. The average efficiency score of environmental pollution
control in eastern China increased from 47.02% to 63.67%, an increase of 26.15%.
This can indicate that there are large differences in environmental pollution control
across China, although local environmental pollution is more serious in central and
western China than in eastern China. However, comparing the average efficiency of
environmental pollution control in the three regions, the relative environmental cost of
economic development is greater in central China and western China, and it is more
difficult to balance high economic development with environmental protection. The
average efficiency score of environmental pollution control in central China increased
from 32.15% to 61.34%, an increase of 47.59%, while the average efficiency score of
environmental pollution control in western China increased from 22.28% to 56.72%,
an increase of 60.72%. This result further reflects that Central China and Western
China are sacrificing the environment to catch up with the economic development of
the Eastern region. At the same time, we find that there are large regional differences
C
S
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efficiency of the ith DMU; is the total number of different types of big data; is the
total number of big data samples. In addition, 34 provincial regions in China are
selected as DMUs in this paper, and the period for analysis is from 2010 to 2020. To
store, manage and analyze environmental pollution big data, we use Spark distributed
computing framework for technical implementation. This paper based on Spark
distributed computing can reduce the overhead caused by data movement and
transparently provide high reliability and high-performance computing for upper-layer
applications
4. ANALYSIS AND DISCUSSION
4.1. OVERALL ENVIRONMENTAL POLLUTION CONTROL
EFFICIENCY PERFORMANCE
To realize the sustainable development of the urban ecological environment, we
introduce big data technology, which should firstly collect the urban ecological
environment data according to the urban environmental pollution situation and the
governance needs, and build the corresponding standard system structure according
to the results obtained from the collection. Finally, pollution treatment should be
completed in strict accordance with the corresponding standard indicators. The
average efficiency scores of environmental pollution control for the whole province of
China, eastern China, central China, and Western China are compiled in Figure 3,
which shows that in the early 21st century, the efficiency of environmental pollution
control in all regions of China was below 50%. With the proposed policies of energy
conservation and emission reduction, carbon peaking, and carbon neutrality in China,
the efficiency of environmental pollution management gradually began to improve
across China. Between 2010 and 2020, the average efficiency score for
environmental pollution control across China's provinces increased from 33.67% to
63.67%, an improvement of 46%. Overall, the efficiency of environmental pollution
control across China is increasing, thanks to strong government support for
environmental protection. The average efficiency score of environmental pollution
control in eastern China increased from 47.02% to 63.67%, an increase of 26.15%.
This can indicate that there are large differences in environmental pollution control
across China, although local environmental pollution is more serious in central and
western China than in eastern China. However, comparing the average efficiency of
environmental pollution control in the three regions, the relative environmental cost of
economic development is greater in central China and western China, and it is more
difficult to balance high economic development with environmental protection. The
average efficiency score of environmental pollution control in central China increased
from 32.15% to 61.34%, an increase of 47.59%, while the average efficiency score of
environmental pollution control in western China increased from 22.28% to 56.72%,
an increase of 60.72%. This result further reflects that Central China and Western
China are sacrificing the environment to catch up with the economic development of
the Eastern region. At the same time, we find that there are large regional differences
C
S
https://doi.org/10.17993/3ctecno.2023.v12n2e44.204-218
in the efficiency of environmental pollution control and its dynamics among Chinese
localities, which generally show a distribution pattern of high in the east and low in the
west.
Figure 3. Changes in the average efficiency scores of environmental pollution control in China
as a whole and in the three major regions
4.2. PERFORMANCE OF ENVIRONMENTAL POLLUTION
CONTROL EFFICIENCY BY PROVINCES AND CITIES
Urban pollution environmental data can accurately reflect the current stage of
urban environmental problems. In turn, it can fully reflect the quantity, quality,
distribution, and other relevant information of various elements in the process of urban
environmental pollution management. In the process of urban ecological
environmental protection, urban pollution data can fully reflect the changing
characteristics of the environment. To facilitate the comparison of environmental
pollution control efficiency in various regions of China, regional differences in
environmental pollution control efficiency in eastern China, central China, and western
China are explored in depth. We extracted the environmental pollution control
efficiency of 17 provinces and municipalities in China for observation and studied the
changes in environmental pollution control efficiency in ten years (2010 to 2020), and
the results are shown in Figure 4. From Figure 4, it can be seen that the city with the
most obvious increase in the efficiency of environmental pollution control within ten
years is Guangdong, which is at the top of the list with an upward relative position
value of 26.47%. This indicates that the Guangdong government has been able to
achieve a common and harmonious development between two hard indicators for
economic development and environmental protection. In addition, the city with the
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weakest increase in environmental pollution control efficiency is Inner Mongolia, with
an increase of 6.89% relative to its position, and little change in environmental
pollution control efficiency compared to the other 16 provinces and cities. The above
results fully indicate that central and western China provinces and cities have
seriously neglected environmental protection while developing their local economies,
resulting in a serious decline in the relative position of environmental pollution control
efficiency. Eastern provinces and cities in China have achieved a relatively
harmonious co-development between environmental protection and economic
development, and have been performing relatively well or have achieved a significant
increase in the relative ranking of environmental pollution control efficiency.
Figure 4. Change in the average efficiency score of environmental pollution control in a region
of China
4.3. ECONOMIC ANALYSIS OF URBAN POLLUTION
ENVIRONMENTAL MANAGEMENT
To comprehensively improve urban pollution environmental management, first of
all, it is necessary to focus on the classification of urban pollutants and the economics
of the recycling process. In the process of building the urban environmental data-
based management system, this part should be the focus. By transferring information
such as the type of urban pollutants collected by the government and relevant
departments to the big data framework, and using this as the basis, we can realize the
analysis of the economics of urban pollutants classification and recycling more
scientifically. Next, the data obtained is analyzed in terms of social group participation
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weakest increase in environmental pollution control efficiency is Inner Mongolia, with
an increase of 6.89% relative to its position, and little change in environmental
pollution control efficiency compared to the other 16 provinces and cities. The above
results fully indicate that central and western China provinces and cities have
seriously neglected environmental protection while developing their local economies,
resulting in a serious decline in the relative position of environmental pollution control
efficiency. Eastern provinces and cities in China have achieved a relatively
harmonious co-development between environmental protection and economic
development, and have been performing relatively well or have achieved a significant
increase in the relative ranking of environmental pollution control efficiency.
Figure 4. Change in the average efficiency score of environmental pollution control in a region
of China
4.3. ECONOMIC ANALYSIS OF URBAN POLLUTION
ENVIRONMENTAL MANAGEMENT
To comprehensively improve urban pollution environmental management, first of
all, it is necessary to focus on the classification of urban pollutants and the economics
of the recycling process. In the process of building the urban environmental data-
based management system, this part should be the focus. By transferring information
such as the type of urban pollutants collected by the government and relevant
departments to the big data framework, and using this as the basis, we can realize the
analysis of the economics of urban pollutants classification and recycling more
scientifically. Next, the data obtained is analyzed in terms of social group participation
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rates using market research, and the proposed measures are revised several times by
integrating the results of the market research. The analyzed economic data is
transmitted to the information. Urban residents, as emitters, should be financially
responsible for the management of the domestic pollution they cause. Therefore, we
have compared the economic analysis of sewage treatment and domestic waste
treatment, which are common in urban pollution. Figure 5 shows the change in urban
pollution treatment costs for urban residents between 2010 and 2020. We can see
that for urban sewage treatment, the cost is significantly higher than the cost of urban
domestic waste treatment. In 2010, residents need to bear the cost of urban sewage
treatment of 283.56 yuan and the cost of garbage treatment of 132.59 yuan. In
comparison, the cost of sewage treatment is 2.14 times higher than the cost of
garbage treatment. The overall trend seems to be that there is a trend toward lowering
the cost of municipal sewage treatment. In 2019, the lowest cost of sewage treatment
that urban residents need to bear is only 208.6 yuan, which is 26.44% lower than the
highest 283.56 yuan in 2010. This indicates that in the process of urban pollution and
environmental management, sewage treatment is becoming more and more efficient,
and the cost that residents need to bear gradually decreases. Similarly, in terms of
urban waste disposal costs, the highest cost required to be spent in 2011 was 176.2
yuan. In 2016, the lowest cost of municipal waste treatment was required to be borne,
requiring 128.9 yuan, a decrease of 26.84% year-on-year. The change in the cost of
urban sewage treatment and urban domestic waste treatment can be seen through
the change in the cost of urban pollution environment treatment that residents need to
bear between 2010 and 2020, with fluctuations of about 30%.
Figure 5. Change in urban pollution treatment costs for urban residents from 2010 to 2020
5. CONCLUSION
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We address air pollution, water pollution, and other pollution sources that need to
be dealt with for urban environmental pollution management. We establish a big data
technology framework for urban environmental pollution treatment, collect relevant
pollution data, and further use the collected data for pollution prevention and
treatment. The results are expressed as follows.
1.
Between 2010 and 2020, thanks to the government's strong support for
environmental protection, the average efficiency score of environmental
pollution control in China's provinces rose from 33.67% to 63.67%, an
efficiency increase of 46%, and the efficiency of environmental pollution control
across China has been rising. At the same time, we find that there are large
regional differences in the efficiency of environmental pollution control and its
dynamics across Chinese localities generally showing a distribution pattern of
high in the east and low in the west.
2.
The environmental pollution control efficiency of 17 provinces and
municipalities in China from 2010 to 2020, Guangdong's environmental
pollution control efficiency increased the most significantly, with a relative
position of 26.47%, which is at the top of the list. Inner Mongolia has the
weakest increase in environmental pollution control efficiency, with an increase
of 6.89% in relative position, and little change in environmental pollution control
efficiency when compared with other 16 provinces and cities.
3. In 2010, residents had to bear the city's sewage disposal cost of $283.56 and
garbage disposal cost of $132.59. In comparison, the cost of sewage treatment
is 2.14 times higher than the cost of garbage treatment. The overall trend
seems to be that there is a trend toward lowering the cost of municipal
wastewater treatment. In 2019, urban residents need to bear the lowest cost of
sewage treatment, which costs only 208.6 yuan, 26.44% lower than the highest
283.56 yuan in 2010. This indicates that the process of urban pollution
environment management, and sewage treatment efficiency is getting higher
and higher, and the cost that residents need to bear gradually decreases.
between 2010 and 2020, the cost of urban pollution environment treatment that
residents need to bear changed significantly, fluctuating at about 30%.
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Shi, J., et al. (2021). Pollution control of wastewater from the coal chemical
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https://doi.org/10.17993/3ctecno.2023.v12n2e44.204-218
3C Tecnología. Glosas de innovación aplicadas a la pyme. ISSN: 2254-4143
Ed.44 | Iss.12 | N.2 April - June 2023
216
We address air pollution, water pollution, and other pollution sources that need to
be dealt with for urban environmental pollution management. We establish a big data
technology framework for urban environmental pollution treatment, collect relevant
pollution data, and further use the collected data for pollution prevention and
treatment. The results are expressed as follows.
1. Between 2010 and 2020, thanks to the government's strong support for
environmental protection, the average efficiency score of environmental
pollution control in China's provinces rose from 33.67% to 63.67%, an
efficiency increase of 46%, and the efficiency of environmental pollution control
across China has been rising. At the same time, we find that there are large
regional differences in the efficiency of environmental pollution control and its
dynamics across Chinese localities generally showing a distribution pattern of
high in the east and low in the west.
2. The environmental pollution control efficiency of 17 provinces and
municipalities in China from 2010 to 2020, Guangdong's environmental
pollution control efficiency increased the most significantly, with a relative
position of 26.47%, which is at the top of the list. Inner Mongolia has the
weakest increase in environmental pollution control efficiency, with an increase
of 6.89% in relative position, and little change in environmental pollution control
efficiency when compared with other 16 provinces and cities.
3. In 2010, residents had to bear the city's sewage disposal cost of $283.56 and
garbage disposal cost of $132.59. In comparison, the cost of sewage treatment
is 2.14 times higher than the cost of garbage treatment. The overall trend
seems to be that there is a trend toward lowering the cost of municipal
wastewater treatment. In 2019, urban residents need to bear the lowest cost of
sewage treatment, which costs only 208.6 yuan, 26.44% lower than the highest
283.56 yuan in 2010. This indicates that the process of urban pollution
environment management, and sewage treatment efficiency is getting higher
and higher, and the cost that residents need to bear gradually decreases.
between 2010 and 2020, the cost of urban pollution environment treatment that
residents need to bear changed significantly, fluctuating at about 30%.
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