Study on Factors Influencing the Quality of Automatic Monitoring Data of Pollution Sources and Technical Assurance Measures

Automatic monitoring data of pollution sources is an important basis for environmental supervision and management.At present,it is difficult to guarantee the quality of automatic monitoring data of pollution sources,and it is difficult to play the role of the monitoring data.In response to this problem,the factors influencing the quality of automatic monitoring data of pollution sources were analyzed in detail,and technical assurance measures for the quality of automatic monitoring data of pollution sources in Shandong Province were studied.Besides,the dynamic management and control idea of automatic monitoring of pollution sources was proposed,and specific technical measures were analyzed from five aspects of standardizing automatic monitoring equipment of pollution sources,improving the data collection and transmission system,establishing a mechanism for reporting operating status information of monitoring equipment,setting alarm rules and alarm processing procedures,and statistically analyzing the operating status of the equipment.Practice has proved that the dynamic management and control system can effectively ensure the quality of automatic monitoring data of pollution sources.

Research on Decision Support System (DSS) of Atmospheric Environment Management in Anhui Province Based on Air Quality Forecasting

With the atmospheric stereoscopic monitoring, air quality forecasting and decision of environment management as the main line, and comprehensive management system as the guidance, five platforms including infrastructure, technological support, monitoring and early monitoring, decision support and information services were established. These platforms have 15 subsystems, including stereoscopic monitoring network, visual business consultation, high-performance computing environment, comprehensive management of atmospheric data, emission inventories of pollu-tion sources, evaluation tools of atmospheric models, monitoring and management of air pollution, forecasting and early warning of air quality, diag-nostic analysis of atmospheric environment, tracking of air pollution sources, emergency management of air pollution, conformity management of air quality, comprehensive display of information, releasing of information to external networks, and releasing of information by mobile networks. The decision support system （DSS） of atmospheric environment management could realize an integration business system of 11 air quality forecast - heavy pollution weather warning - diagnosis of pollution causes （dynamic analysis of pollution sources） -air quality conformity planning （air pollu-tion emergency management） -evaluation of forecasting and warning results （evaluation pf management measures） -air quality forecasting＂ and provide the technical support for the prevention and control of atmosphere pollution in Anhui province.

Air Quality Monitoring and Its Implication on the Environmental Licensing Process in Brazil

In the state of Sao Paulo, Brazil, public policies regarding the air quality aimed at the welfare of the population are strongly dependent on monitoring conducted by the Sao Paulo State Environmental Company (CETESB), which can be influenced by faulty monitors and equipment support and cuts in power supply, among others. A research conducted from 1998 to 2008 indicated that a significant portion of the air quality automatic stations in the state of Sao Paulo did not meet the criterion of representativeness of measurements of PM10, NO2, O3, CO and SO2 concentrations which resulted in the classification of some municipalities as the nonattainment area, a situation evidenced for PM10 and O3 parameters. The network unavailability for each parameter was estimated and compared with the monitoring networks operated in Canada and the UK. This paper discusses the implications of the lack of representativeness of measurements in the environmental licensing process of pollution sources from 2008, when by the effect of state law, municipalities have been qualified according to their air quality nonattainment level.

Big Data Analytics with Artificial Intelligence Enabled Environmental Air Pollution Monitoring Framework

Environmental sustainability is the rate of renewable resourceharvesting, pollution control, and non-renewable resource exhaustion. Airpollution is a significant issue confronted by the environment particularlyby highly populated countries like India. Due to increased population, thenumber of vehicles also continues to increase. Each vehicle has its individualemission rate;however, the issue arises when the emission rate crosses thestandard value and the quality of the air gets degraded. Owing to the technological advances in machine learning (ML), it is possible to develop predictionapproaches to monitor and control pollution using real time data. With thedevelopment of the Internet of Things (IoT) and Big Data Analytics (BDA),there is a huge paradigm shift in how environmental data are employed forsustainable cities and societies, especially by applying intelligent algorithms.In this view, this study develops an optimal AI based air quality prediction andclassification (OAI-AQPC) model in big data environment. For handling bigdata from environmental monitoring, Hadoop MapReduce tool is employed.In addition, a predictive model is built using the hybridization of ARIMAand neural network (NN) called ARIMA-NN to predict the pollution level.For improving the performance of the ARIMA-NN algorithm, the parametertuning process takes place using oppositional swallow swarm optimization(OSSO) algorithm. Finally, Adaptive neuro-fuzzy inference system (ANFIS)classifier is used to classify the air quality into pollutant and non-pollutant.A detailed experimental analysis is performed for highlighting the betterprediction performance of the proposed ARIMA-NN method. The obtainedoutcomes pointed out the enhanced outcomes of the proposed OAI-AQPCtechnique over the recent state of art techniques.

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.

Comprehensive evaluation method of urban air quality statistics based on environmental monitoring data and its application

Air quality monitoring is effective for timely understanding of the current air quality status of a region or city.Currently,the huge volume of environmental monitoring data,which has reasonable real-time performance,provides strong support for in-depth analysis of air pollution characteristics and causes.However,in the era of big data,to meet current demands for fine management of the atmospheric environment,it is important to explore the characteristics and causes of air pollution from multiple aspects for comprehensive and scientific evaluation of air quality.This study reviewed and summarized air quality evaluation methods on the basis of environmental monitoring data statistics during the 13th Five-Year Plan period,and evaluated the level of air pollution in the Beijing-Tianjin-Hebei region and its surrounding areas(i.e.,the“2+26”region)during the period of the three-year action plan to fight air pollution.We suggest that air quality should be comprehensively,deeply,and scientifically evaluated from the aspects of air pollution characteristics,causes,and influences of meteorological conditions and anthropogenic emissions.It is also suggested that a threeyear moving average be introduced as one of the evaluation indexes of long-term change of pollutants.Additionally,both temporal and spatial differences should be considered when removing confounding meteorological factors.

Air Pollution in Major Chinese Cities: Some Progress, But Much More to Do

Background: Ambient (outdoor) air pollution has been implicated as a major cause of acute cardiovascular and pulmonary illnesses and increased risk for acute and chronic effects after chronic exposures, including mortality and morbidity. In 2008, due to persistent health concerns about its workforce and their dependents, the US Mission in China began monitoring air quality at the US Embassy in Beijing. Subsequently, monitoring stations were also established at US consulates at Shanghai (2011), Guangzhou (2011), Chengdu (2012), and Shenyang (2013). Objectives: To determine whether there have been definable trends in air quality in these five Chinese cities. Methods: Air monitoring results from each locale for accumulated PM2.5 particulate matter were calculated hourly. Accumulated data were organized, culled using a standardized set of heuristics, and analyzed for trends. Results: China’s capital city, Beijing, experienced decreased PM2.5 from 2013 through 2015, but no significant long-term downward trend from 2008 through 2015. Shanghai has not shown any definable air quality trend since 2012. Chengdu experienced some improvement in air quality since 2013, but none discernible from 2012 through 2015. Guangzhou had generally better air quality, and a downward trend since 2012. Shenyang experienced increasingly severe air pollution from 2013 through 2015. Conclusion: There appear to have been recent tangible, though modest, improvements in air quality in three large Chinese cities: Beijing, Chengdu, and Guangzhou, but no apparent progress in Shanghai, and a worrisome decline in air quality observed in Shenyang. Despite recent progress, there is a long way to go before even the cities which show improvement reach Chinese standards.

基于校园PM_(10)监测及重金属风险评价的综合性教学实验设计

本综合性实验以大学校园大气中颗粒物作为研究对象,探究了校园不同功能区内颗粒物的分布情况,分析了颗粒物中重金属的含量,对暴露在此环境下学生的健康风险进行了评估。该综合性实验与实际问题紧密结合,强化实验设计原则、采样点设置、监测方法、元素分析和环境影响评价等知识点,有助于调动学生主观能动性,能够使学生体会学有所用、学以致用,从而提升了他们的学习兴趣,优化课程实验教学效果。

环境保护工程空气监测现场的质量控制探析

如今,空气污染问题已经成为全球密切关注的热点,严重威胁着人类健康、生态环境等。因此,必须严格把关环境保护工程的现场空气监测质量。环境保护工程空气监测是确保空气质量符合标准的关键任务,它涉及采样、仪器校准、数据收集和分析等方面。本文分析了空气监测现场质量管控存在的问题,并提出相应的质量控制措施,为环境保护工作提供科学依据。

环境检测技术在水质、监测中的应用研究

随着工业化进程的加速和城市化水平的提升,环境污染问题日益严重。环境检验检测是重要的手段,用于识别和控制污染,在污染源监测与治理中发挥着关键作用。然而,环境检验检测仍面临检测技术、数据标准化和监测网络等方面的挑战。基于此,文章对环境检验检测在污染源监测与治理中的作用进行了深入分析,并提出了相应的对策建议,以期提高环境检验检测能力,从而有效应对环境污染问题,促进可持续发展。

大气污染防治网格化监测的运用分析

随着大气污染的日趋严重,在实际治理过程中,需要进行精细化地防治与管理,重点加强对大气污染的监测,并通过数据采集工作,提升大气污染治理的有效性。基于此,本文阐述了大气污染防治网格化监测技术,分析了大气污染网格化监测的功能和技术要求,并对该技术的应用途径进行了探讨,通过结合实际案例分析了网格化监测的治理成效,以期为相关人员提供参考。

环境保护工程中空气监测现场的质量控制对策研究

社会经济的高速发展会提升了人们改造自然的能力,但也会给自然环境带来严重影响。在环境保护工程中,空气监测属于评估环境空气质量、预防和控制空气污染的重要手段,唯有有序进行才能保证空气监测的质量。基于此,本文主要对环保工程的空气监测进行简要叙述,分析空气监测现场质量控制的意义,并深层次探究空气监测现场的质量控制对策,以期解决空气污染问题,促进环境保护工程的发展。

关于对我国环境自动监测发展的思考

本文对我国环境自动监测发展进行了全面思考和分析。首先,强调了环境质量自动监测系统建设的重要性。其次,分析了环境自动监测存在的问题,包括企业推广、监管模式和监测方法等方面的问题。然后,阐述了对我国环境自动监测发展的认识,包括发展势头迅猛、国产设备前景广阔、标准化和规范化问题、建设速度控制以及数据共享问题等关键点。最后,提出了必要的改进措施,加强对自动监测系统的监控管理以及理顺自动监测系统的管理体制和运行机制,为环境自动监测的可持续发展提供了思路和建议。

A methodological framework for improving air quality monitoring network layout.Applications to environment management

This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network(AQMN).It requires to be constituted by a minimum and reliable number of measurement sites.Nevertheless,the AQMN efficiency should be assessed over time,as a consequence of the possible emergence of new emission sources of air pollutants,which could lead to variations on their spatial distribution within the target area.PM_(10)particles data monitored by the Community of Madrid's(Spain)AQMN between 2008 and 2017 were used to develop a methodology to optimize the AQMN performance.The annual spatial distribution of average PM_(10)levels over the studied period monitored by all current stations vs those more representative was provided by a geographic information system(GIS),and the percentage of similarity between both postulates was quantified using simple linear regression(>95%).As one innovative tool of this study,the practical application of the proposed methodology was validated using PM_(10)particles data measured by AQMN during 2007 and 2018,reaching a similitude degree higher than 95%.The influence of temporal variation on the proposed methodological framework was around 20%.The proposed methodology sets criteria for identifying non-redundant stations within AQMN,it is also able to appropriately assess the representativeness of fixed monitoring sites within an AQMN and it complements the guidelines set by European legislation on air pollutants monitoring at fixed stations,which could help to tackle efforts to improve the air quality management.

环境工程中空测现场的质量控制分析

在环境工程领域,空气质量监测是评估和管理空气环境的重要手段,而空气质量监测现场是获取准确监测数据的基础,它直接关系到监测结果的可靠性和有效性。因此,对于空气监测现场进行质量控制分析是确保监测数据准确性和可比性的关键环节。通过对监测现场的质量控制分析,可以及时发现并解决潜在问题,提高监测数据的可信度和可靠性,为制定环境保护决策提供准确的依据。本研究旨在探讨空气监测现场的质量控制分析,提高空气监测数据的准确性、可靠性和可比性。

探析环境保护工程空气监测现场的质量控制

本文探讨了环境保护工程中空气监测现场的质量控制,并提出了一系列对策。首先说明了空气监测工作对环境保护和人类健康的重要性,然后重点分析了空气监测现场质量控制的重要性和存在的问题,最后提出了解决问题的策略,包括做好前期准备工作、设定好采样时间和频率、制定新的环保理念、引入先进的采样技术、强化采样工作质量控制力度和质量控制人员培训与管理等方面的措施。

环境空气自动监测中的质量保证和质量控制研究

工业的快速发展对生存环境造成了严重污染。当前,大多数城市的灰霾现象比较严重,不仅影响城市环境,而且对人体健康也有很大的影响。因此,开展环境空气自动监测对于全面掌握该地区的空气质量状况、预测其发展趋势、制定防治对策、改善空气质量具有十分重要的意义。

中国城市环境空气质量自动监测现状及发展

伴随中国飞速的城市化发展,环境空气污染严重影响居民的身心健康及生活质量。为了有效控制城市空气污染,保障居民的呼吸健康,深化城市环境空气质量自动监测应用研究显得颇为关键。文章首先,概述中国城市环境空气质量监测发展历程的三个基本阶段;其次,举例论述空气污染“城市病”的成因及危害,并对比分析各种自动监测技术的优势及不足;最后,探究其发展趋势及未来展望,旨在为城市环境空气质量自动监测应用研究提供借鉴。

浅析如何做好水质环境监测的质量保证

水质监测是环境监测的重要内容,主要是对地表水、地下水以及污水等进行水质指标的检测,并通过科学、合理的分析方法对水质进行评价。水质监测的目的是对环境质量状况进行评价,为环境管理、决策提供科学依据。为了保证水质监测数据的准确性和科学性,必须建立质量保证体系,提高人员素质,对技术和方法进行有效控制,并加强环境监测质量管理。其中质量保证体系包括组织保证体系、技术保障体系和管理保障体系等。水质环境监测质量管理包括过程控制和结果控制两个方面。本文针对如何做好水质环境监测的质量保证进行分析讨论,并提出了相关建议。

自动监控技术在环境保护中的应用与发展

自动监控技术在环境保护中发挥着重要作用。通过传感器和数据采集系统,可以实时监测污染源、环境质量和垃圾处理等领域,并提供准确的数据和预警信息。随着技术的发展,自动监控技术将进一步应用于数据智能分析、无人机监测和数据共享与公共服务。