Emission Control Measures Research Articles

Ionic Liquid-Based Green Solvents for Extraction and Purification of Natural Plant Products

Introduction: This research paper explores the environmental sustainability of ionic liquid-based green solvents in the extraction and purification of natural plant products, with a focus on their entire life cycle. The objectives of the study were to assess the environmental impact of ionic liquid synthesis, energy consumption, water usage, emissions, recycling rates, policy effects, and stakeholder perceptions. Methods: Methodologically, we conducted a comprehensive Life Cycle Assessment (LCA) that involved primary data collection through field surveys and interviews with key stakeholders in the ionic liquid production and usage industry across various regions in India. The data were analyzed using specialized LCA software tools to quantify environmental impacts. Key findings include the identification of synthesis as a major contributor to environmental impact, emphasizing the need for greener synthesis methods. Results: The study revealed the significant carbon footprint, energy consumption, and water usage during production, highlighting opportunities for improvement. Emissions data underscored the importance of emission control measures, particularly for greenhouse gases and volatile organic compounds. Recycling and reuse were identified as environmentally friendly disposal methods. Policy compliance varied among stakeholders, indicating room for stricter regulations. Stakeholder perceptions varied, with researchers having the most positive outlook. Implications of the findings extend to sustainable chemistry practices, emphasizing interdisciplinary collaboration and the importance of considering the entire life cycle of chemical processes. Conclusion: This research contributes to a deeper understanding of green solvents and provides a foundation for promoting sustainable practices in industrial processes in India and globally.

Impacts of the East Asia monsoon on the PM2.5 acidity in Hanoi

This study investigates the acidity of particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) in Hanoi, the capital city of Vietnam, and its influencing factors by analyzing measured concentrations of water-soluble inorganic ions (WSIIs) in 107 24-h samples collected between June 2021 and February 2022. The average sulfate, nitrate, and ammonium concentrations were 5.79, 3.55, and 5.46 μg m−3, respectively. Among the samples, 83 exhibited alkaline aerosols characterized by elevated ammonium-to-sulfate molar concentration ratios (ASMCR) ranging from 2.3 to 9.6, while 24 showed acidic characteristics with ASMCR ranging from 0.5 to 2.5. By employing the Extended Aerosol Inorganic Model E-AIM III, with major WSIIs as the input parameters, the estimated aerosol acidity pH ranged from 8.6 to 10.9 for alkaline aerosols and below 4.5 for acidic aerosols. These variations in ASMCR and aerosol pH highlight the distinct acidic and alkaline aerosol source regions affecting Hanoi's PM2.5 by the monsoon air masses. The Potential Source Contribution Function (PSCF) maps of NH4+ and SO42− revealed the Northeast and Southeast monsoon upwind sources of acidic aerosols over China's Guangdong coastal region and Vietnam's offshore, respectively. Alkaline aerosols were observed during the Northeast and Southwest monsoons, with upwind sources originating in South China, Thailand, and Cambodia. The emergence of the ammonium-rich source areas in South China may be attributed to China's sustained emission control measures, targeting acidic SO2 and NOx emissions while leaving alkaline NH3 emissions largely unaffected. This research provided insights into the intricate relationships between regional emissions, long-range transport, and local meteorological-driven emissions, offering valuable guidance for effective air quality management in urban environments.

Morphology and chemical composition of mineral particles in a special dust storm with high relative humidity in North China

A special dust storm characterized by high PM10 mass concentrations (921.9 ± 632.3 μg m−3) and high relative humidity (RH; 60.1 % ± 11.1 %) was observed on March 22–24, 2023 at a coastal city of North China. Aerosol particles of PM10 were analyzed by a scanning electron microscope coupled with energy dispersive X-ray and an ion chromatograph. The results showed that individual mineral particles were dominated by clay minerals, followed by quartz, feldspar, and carbonate. Bulk water-soluble inorganic ions analysis showed that SO42- mass concentrations varied from 3.7 μg m−3 to 23.3 μg m−3 with an average value of 12.4 μg m−3. However, their mass ratios to PM10 were relatively stable, being 1.15–2.01 % with an average value of 1.49 % ± 0.25 %, similar to the value near the dust sources (Tengger Desert). Although S-containing individual mineral dust varied from 5.2 % to 70.7 %, the average weight ratio of S on individual mineral dust was 2.1 %, much lower than that of non-dust periods (11.0 %). The results suggested limited sulfate formation on mineral dust surfaces even under high RH. In contrast, NO3-, which was very limited in dust sources, varied from 0.21 % to 4.11 % of the total PM10 with an average value of 1.61 % ± 1.07 %. The research highlighted that nitrate formation has exceeded sulfate formation during severe dust storm episodes, which might because the atmospheric compositions in China have changed significantly with a high mass ratio of NO2/SO2 after the implementation of the strict emission control measures.

IoT - Toxic Gas Detection System in Sewage

The application of IoT and machine learning in gas detection systems for sewage offers an innovative approach to real-time gas detection and enhances environmental safety in industrial and urban environments. This system uses advanced technologies such as the Internet of Things (IoT), machine learning algorithms, and high-performance sensors like the MQ135 and the DHT11 to achieve the best results in the gas concentration measurement and collection. It identifies abnormalities and determines which emission control measures are most effective for specific release points and similar situations. The design of the device includes sensor nodes that are primarily responsible for data collection and a central microcontroller (MCU) that operates a machine learning algorithm for efficient anomaly detection and predictive maintenance. The system uses the IoT connection to regularly send data to cloud platform (Blynk), enabling real time monitoring of gas levels and environmental conditions. The system generates a visual image of the captured data that can be accessed online. Distinctive attributes like accurate gas detection, continuous monitoring, predictive maintenance, remote assessment, and comprehensive data visualization, all contribute to smart decision-making for environmental safety.

Environmental forcing and policy synergy: A multidimensional approach in the governance of air pollution and carbon emission

Policy synergies effectively contribute to the integrated management of air pollution and carbon emissions, which is crucial for safeguarding ecosystem stability and public health. This study uses the causal network model of Gaussian process regression to analyze the combined impacts of dynamic and static carbon emission reduction and air quality policies on carbon emissions and air quality. The causal effects of policy measures and their synergistic effects are also examined. The study results indicate: (1) There is significant geographical heterogeneity in the implementation of environmental policies and regional economic development, with the economically developed eastern coastal regions adopting more stringent carbon emission and air pollution control measures, while the western provinces adopt relatively lax environmental policies. (2) The synergistic effect of carbon emission reduction policies and air quality policies exists, and the two types of static policies are substitutable for managing carbon dioxide emissions and air pollution. (3) Policies' forced effect exists, where the exacerbation of environmental problems leads to the formation and implementation of policies. (4) The value added by the secondary industry is a key motivation for forming carbon emission reduction policies and air quality control policies. Additionally, the value added by the secondary industry directly impacts the incidence of respiratory diseases (e.g., tuberculosis). Finally, dynamic and synergistic policy recommendations are proposed based on the study's findings.

Measurement report: Impact of emission control measures on environmental persistent free radicals and reactive oxygen species – a short-term case study in Beijing

Measurement report: Impact of emission control measures on environmental persistent free radicals and reactive oxygen species – a short-term case study in Beijing

Spatial variation, emissions, transport, and risk assessment of organophosphate esters in two large petrochemical complexes in southern China

Organophosphate esters (OPEs) serve as significant flame retardants and plasticizers in various petrochemical downstream products. The petrochemical industry could be a potential source of atmospheric OPEs, but their emissions from this industry are poorly understood. The present study revealed the spatial variation, emission, and atmospheric transport of traditional and novel OPEs (TOPEs and NOPEs, respectively) in atmospheric particulate matter (PM) across Hainan and Guangdong petrochemical complexes (HNPC and GDPC, respectively) in southern China. The total concentrations of TOPEs ranged from 232 to 46,002 pg/m3 and from 200 to 20,347 pg/m3 in the HNPC and GDPC, respectively, which were substantially higher than those of NOPEs (HNPC: 23.5−147 pg/m3, GDPC: 13.9−465 pg/m3). Enterprises involved in the production of downstream petrochemical products presented relatively high concentrations of OPEs, indicating evident emissions of these pollutants in the petrochemical industry. The correlations of PM-bound OPEs in the atmosphere are determined mainly by their coaddition to industrial products or their coexistence in technical mixtures. The annual emissions of TOPEs and NOPEs in the HNPC were 42.6 kg and 0.34 kg, respectively, and those in the GDPC were 116 kg and 1.85 kg, respectively. OPEs from the HNPC can reach Vietnam, Cambodia, and Guangxi Province, China, and those from the GDPC can reach Guangxi Province and Hunan Province via atmospheric transmission after 24 h of emission. The OPE concentrations reaching the receptor regions were generally less than 3.20 pg/m3. Risk assessment revealed that OPE inhalation exposure on two petrochemical complexes likely poses minor risks for people living in the study areas, but the risk resulting from two chlorinated OPEs should be noted since they are close to the threshold values. This study has implications for enhancing control measures for OPE emissions to reduce health risks related to the petrochemical industry.

Combating air pollution significantly reduced air mercury concentrations in China.

In the past decade, China has motivated proactive emission control measures that have successfully reduced emissions of many air pollutants. For atmospheric mercury, which is a globally transported neurotoxin, much less is known about the long-term changes in its concentrations and anthropogenic emissions in China. In this study, over a decade of continuous observations at four Chinese sites show that gaseous elemental mercury (GEM) concentrations continuously increased until the early 2010s, followed by significant declines at rates of 1.8%-6.1% yr-1 until 2022. The GEM decline from 2013 to 2022 (by 38.6%±12.7%) coincided with the decreasing concentrations of criteria air pollutants in China and were larger than those observed elsewhere in the northern hemisphere (5.7%-14.2%). The co-benefits of emission control measures contributed to the reduced anthropogenic Hg emissions and led to the GEM decline in China. We estimated that anthropogenic GEM emissions in China were reduced by 38%-50% (116-151 tons) from 2013 to 2022 using the machine-learning and relationship models.

Enhanced Aging of Black Carbon under Recent Clean Air Actions and Future Carbon Neutrality Scenario in China.

China has implemented strict emission control measures, but it is unclear how they affect black carbon (BC) aging and light absorption. Here, we use the Community Atmosphere Model version 6 (CAM6) with the four-mode version of the Modal Aerosol Module coupled with machine learning (MAM4-ML) to simulate BC aging during 2011-2018 and 2050/2100 following a carbon neutrality scenario (SSP1-2.6), respectively. During 2011-2018, the mass ratio of coatings to BC (RBC) widely increased (5.4% yr-1) over the east of China. The increased secondary organic aerosol (SOA) coatings dominate (88%) the increased RBC, while the sulfate coatings decrease. The drivers of BC coating changes come from the different magnitudes of emission reductions in secondary aerosol precursors (i.e., volatile organic compounds (VOCs) and SO2) and BC. During 2011-2018, the increased RBC enhances the BC mass absorption cross section (MAC, 0.7% yr-1). In 2050/2100 for SSP1-2.6, emission control leads to further increased RBC (95/145%) and BC MAC (12/17%). For both 2011-2018 and 2050/2100, the enhanced BC MAC partly offsets the declining direct radiative effect (DRE) of BC due to direct emission reduction. As a result, the full impact of direct emission reductions of BC on BC DRE is only 75% for 2011-2018 and 90/94% for 2050/2100.

Identifying Driving Factors of Atmospheric N2O5 with Machine Learning.

Dinitrogen pentoxide (N2O5) plays an essential role in tropospheric chemistry, serving as a nocturnal reservoir of reactive nitrogen and significantly promoting nitrate formations. However, identifying key environmental drivers of N2O5 formation remains challenging using traditional statistical methods, impeding effective emission control measures to mitigate NOx-induced air pollution. Here, we adopted machine learning assisted by steady-state analysis to elucidate the driving factors of N2O5 before and during the 2022 Winter Olympics (WO) in Beijing. Higher N2O5 concentrations were observed during the WO period compared to the Pre-Winter-Olympics (Pre-WO) period. The machine learning model accurately reproduced ambient N2O5 concentrations and showed that ozone (O3), nitrogen dioxide (NO2), and relative humidity (RH) were the most important driving factors of N2O5. Compared to the Pre-WO period, the variation in trace gases (i.e., NO2 and O3) along with the reduced N2O5 uptake coefficient was the main reason for higher N2O5 levels during the WO period. By predicting N2O5 under various control scenarios of NOx and calculating the nitrate formation potential from N2O5 uptake, we found that the progressive reduction of nitrogen oxides initially increases the nitrate formation potential before further decreasing it. The threshold of NOx was approximately 13 ppbv, below which NOx reduction effectively reduced the level of night-time nitrate formations. These results demonstrate the capacity of machine learning to provide insights into understanding atmospheric nitrogen chemistry and highlight the necessity of more stringent emission control of NOx to mitigate haze pollution.

It's time to reevaluate the list of priority polycyclic aromatic compounds: Evidence from a large urban shallow lake

Monitoring only 16 priority PAHs (Pri-PAHs) may greatly underestimate the pollutant load and toxicity of polycyclic aromatic compounds (PACs) in aquatic environments. There is an urgent need to reevaluate the list of priority PACs. To determine which PACs deserve priority monitoring, the occurrence, sources, and toxicity of 78 PACs, including 24 parent PAHs (Par-PAHs), 49 alkylated PAHs (Alk-PAHs), 3 oxygenated PAHs (OPAHs), carbazole, and dibenzothiophene were investigated for the first time in Lake Chaohu sediments, China. Concentrations of ∑Par-PAHs, ∑Alk-PAHs, and ∑OPAHs ranged from 35 to 165, 3.4–26, and 7.7–26 ng g−1, respectively. Concentrations of 16 Pri-PAHs have decreased by 1–2 orders of magnitude compared to a decade ago, owing to the effective implementation of PAHs emission control measures. Comparisons with the sediment quality guidelines indicated that 16 Pri-PAHs have negligible adverse effects on benthic organisms. Positive matrix factorization (PMF) model results showed that coal combustion was the major source of PACs (accounting for 23.5 %), followed by traffic emissions (23.4 %), petroleum volatilization (21.9 %), wood/biomass combustion (18.2 %), and biological/microbial transformation (13.1 %). The toxicity of PACs was assessed by calculating the BaP toxic equivalent concentrations (TEQBaP) and toxic units. It was found that Par-PAHs were the predominant toxic substances. In addition, monomethyl-BaPs, OPAHs, BeP, and 7,12-DMBaA should be prioritized for monitoring due to their noticeable contributions to overall toxicity. The contributions of different sources to the toxicity of PACs were determined based on PMF model results and TEQBaP values, which revealed that combustion sources mainly contributed to the comprehensive toxicity of PACs in Lake Chaohu sediments.

Obscured Contribution of Oxygenated Intermediate-Volatility Organic Compounds to Secondary Organic Aerosol Formation from Gasoline Vehicle Emissions.

Secondary organic aerosol (SOA) formation from gasoline vehicles spanning a wide range of emission types was investigated using an oxidation flow reactor (OFR) by conducting chassis dynamometer tests. Aided by advanced mass spectrometric techniques, SOA precursors, including volatile organic compounds (VOCs) and intermediate/semivolatile organic compounds (I/SVOCs), were comprehensively characterized. The reconstructed SOA produced from the speciated VOCs and I/SVOCs can explain 69% of the SOA measured downstream of an OFR upon 0.5-3 days' OH exposure. While VOCs can only explain 10% of total SOA production, the contribution from I/SVOCs is 59%, with oxygenated I/SVOCs (O-I/SVOCs) taking up 20% of that contribution. O-I/SVOCs (e.g., benzylic or aliphatic aldehydes and ketones), as an obscured source, account for 16% of total nonmethane organic gas (NMOG) emission. More importantly, with the improvement in emission standards, the NMOG is effectively mitigated by 35% from China 4 to China 6, which is predominantly attributed to the decrease of VOCs. Real-time measurements of different NMOG components as well as SOA production further reveal that the current emission control measures, such as advances in engine and three-way catalytic converter (TWC) techniques, are effective in reducing the "light" SOA precursors (i.e., single-ring aromatics) but not for the I/SVOC emissions. Our results also highlight greater effects of O-I/SVOCs to SOA formation than previously observed and the urgent need for further investigation into their origins, i.e., incomplete combustion, lubricating oil, etc., which requires improvements in real-time molecular-level characterization of I/SVOC molecules and in turn will benefit the future design of control measures.

Joint effects of traffic-related air pollution and hypertensive disorders of pregnancy on maternal postpartum depressive and anxiety symptoms.

Ambient air pollution has been linked to postpartum depression. However, few studies have investigated the effects of traffic-related NOx on postpartum depression and whether any pregnancy-related factors might increase susceptibility. To evaluate the association between traffic-related NOx and postpartum depressive and anxiety symptoms, and effect modification by pregnancy-related hypertension. This study included 453 predominantly low-income Hispanic/Latina women in the MADRES cohort. Daily traffic-related NOx concentrations by road class were estimated using the California LINE-source dispersion model (CALINE4) at participants' residential locations and averaged across pregnancy. Postpartum depressive and anxiety symptoms were evaluated by a validated questionnaire (Postpartum Distress Measure, PDM) at 1, 3, 6 and 12 months postpartum. Multivariate linear regressions were performed to estimate the associations at each timepoint. Interaction terms were added to the linear models to assess effect modification by hypertensive disorders of pregnancy (HDPs). Repeated measurement analyses were conducted by using mixed effect models. We found prenatal traffic-related NOx was associated with increased PDM scores. Specifically, mothers exposed to an IQR (0.22 ppb) increase in NOx from major roads had 3.78% (95% CI: 0.53-7.14%) and 5.27% (95% CI: 0.33-10.45%) significantly higher 3-month and 12-month PDM scores, respectively. Similarly, in repeated measurement analyses, higher NOx from major roads was associated with 3.06% (95% CI: 0.43-5.76%) significantly higher PDM scores across the first year postpartum. Effect modification by HDPs was observed: higher freeway/highway and total NOx among mothers with HDPs were associated with significantly higher PDM scores at 12 months postpartum compared to those without HDPs. This study shows that prenatal traffic-related air pollution was associated with postpartum depressive and anxiety symptoms. The study also found novel evidence of greater susceptibility among women with HDPs, which advances the understanding of the relationships between air pollution, maternal cardiometabolic health during pregnancy and postpartum mental health. Our study has potential implications for clinical intervention to mitigate the effects of traffic-related pollution on postpartum mental health disorders. The findings can also offer valuable insights into urban planning strategies concerning the implementation of emission control measures and the creation of green spaces.

Impact of Meteorological Conditions on PM2.5 Pollution in Changchun and Associated Health Risks Analysis

The escalating concern regarding increasing air pollution and its impact on the health risks associated with PM2.5 in developing countries necessitates attention. Thus, this study utilizes the WRF-CMAQ model to simulate the effects of meteorological conditions on PM2.5 levels in Changchun, a typical city in China, during January 2017 and January 2020. Additionally, it introduces a novel health risk-based air quality index (NHAQI) to assess the influence of meteorological parameters and associated health risks. The findings indicate that in January 2020, the 2-m temperature (T2), 10-m wind speed (WS10), and planetary boundary layer height (PBLH) were lower compared to those in 2017, while air pressure exhibited a slight increase. These meteorological parameters, characterized by reduced wind speed, heightened air pressure, and lower boundary layer height—factors unfavorable for pollutant dispersion—collectively contribute to the accumulation of PM2.5 in the atmosphere. Moreover, the NHAQI proves to be more effective in evaluating health risks compared to the air quality index (AQI). The annual average decrease in NHAQI across six municipal districts from 2017 to 2020 amounts to 18.05%. Notably, the highest health risks are observed during the winter among the four seasons, particularly in densely populated areas. The pollutants contributing the most to the total excess risk (ERtotal) are PM2.5 (45.46%), PM10 (33.30%), and O3 (13.57%) in 2017, and PM2.5 (67.41%), PM10 (22.32%), and O3 (8.41%) in 2020. These results underscore the ongoing necessity for PM2.5 emission control measures while emphasizing the importance of considering meteorological parameters in the development of PM2.5 reduction strategies.

Nighttime ozone excess days and the associated meteorological conditions in the North China Plain from 2015 to 2022

We examined the spatial and temporal variations of nighttime ozone (O3) excess days (NOEDs) in the North China Plain (NCP) during 2015–2022 by using the observed O3 concentrations from the China National Environmental Monitoring Center network. The NOEDs were defined as those with any 1-h average O3 concentration at night (20:00 to 06:00 local time) exceeding 200 μg m−3. The observations showed that the annual frequencies of NOEDs averaged over the 57 cities in the NCP were 1.56, 1.72, 6.23, 6.53, 8.84, 5.93, 5.07, and 6.86 days in 2015, 2016, 2017, 2018, 2019, 2020, 2021, and 2022, respectively, with a linear increasing trend of 0.66 d y−1. Using the K-means clustering method, two typical regional NOEDs types in the NCP were identified. Type1 had the highest frequencies of NOEDs in the southwest of NCP, while Type2 had the highest frequencies in the central NCP region. These two types contributed to 53.5% and 46.5% of the regional NOEDs in NCP, respectively. Compared with the regional non-NOEDs (with nighttime O3 did not exceed but daytime O3 exceeded O3 air quality standard), both Type1 and Type2 NOEDs generally had higher temperature, lower relative humidity, and higher planetary boundary height in both afternoon and night, favoring the production and accumulation of O3 in the afternoon as well as the persistent high O3 at night. Corresponding weather patterns were also identified. These results have important implications for emission control strategies during NOEDs. Emission control measures can be applied once the dominant circulation patterns have been predicted.

Designing regional joint prevention and control schemes of PM2.5 based on source apportionment of chemical transport model: A case study of a heavy pollution episode

Fine particular matter (PM2.5) pollution still occurs frequently in China. Despite recognizing the importance of regional joint prevention and control (RJPC) for mitigating haze pollution, there is still a limited understanding of scheme design and effectiveness. In this study, with the Fenhe Plain in China serving as the case, the Integrated Source Apportionment Method (ISAM), incorporated into the Community Multiscale Air Quality Modeling System (CMAQ), was used to quantitively identify PM2.5 sources during a typical heavy pollution episode from Jan. 20th to 25th, 2021. Informed by source apportionment, we designed and assessed multiple RJPC scenarios for eliminating heavy pollution, yielding recommended RJPC schemes. Source apportionment results revealed a substantial increase in the contribution percentage of regions within a 350-km radius during the pollution episode compared to the non-polluted period. Sulfate was predominantly contributed from long-distance transport, whereas nitrate was chiefly contributed from closer regions. Ammonium exhibited higher local contributions than nitrate from the Fenhe Plain. Moreover, Taiyuan and Linfen were identified as PM2.5 exporters, whereas Sanmenxia, Jinzhong, and Luliang served as PM2.5 importers, and Yuncheng acted as a comprehensive city. The proposed specific RJPC schemes aimed at eliminating heavy pollution for the Fenhe Plain emphasized the importance of controlling emissions of particulate matter, ammonia, nitrogen oxides, and volatile organic compounds in areas within an approximate 350-km radius outside the Fenhe Plain, in addition to strengthening the local emission control. Nevertheless, only through the comprehensive and in-depth implementation of emission control measures across a larger area can PM2.5 compliance be achieved.

Long-term variations of air pollutants and public exposure in China during 2000–2020

Since 2000, China has faced severe air pollution challenges，prompting the initiation of comprehensive emission control measures post-2013. The subsequent implementation of these measures has led to remarkable enhancements in air quality. This study aims to enhance our understanding of the long-term trends in fine particulate matter (PM2.5) and gaseous pollutants of ozone (O3) and nitrogen dioxide (NO2) across China from 2000 to 2020. Utilizing the Community Multiscale Air Quality (CMAQ) model, we conducted a nationwide analysis of air quality, systematically quantifying model predictions against observations for pollutants. The CMAQ model effectively captured the trends of air pollutants, meeting recommended performance benchmarks. The findings reveal variations in pollutant concentrations, with initial increases in PM2.5 followed by a decline after 2013. The proportion of the population living in high PM2.5 concentrations (>75 μg/m3) decreased to <5 % after 2015. However, during the period from 2017 to 2020, around 40 % of the population continued to live in regions that did not meet the criteria for Chinese air quality standards (35 μg/m3). From 2000 to 2019, fewer than 20 % of the population met the WHO standard (100 μg/m3) for MDA8 O3. In 2000, 77 % of the population met the NO2 standard (<20 μg/m3), a figure that declined to 60 % between 2005 and 2014, nearly reaching 70 % in 2020. This study offers a comprehensive analysis of the changes in pollutants and public exposure in 2000–2020. It serves as a foundational resource for future efforts in air pollution control and health research.

Geo-visualizing the hotspots of smog-induced health effects in district Gujranwala, Pakistan: a community perspective.

This study aims to examine the health effects of smog on different age groups in Gujranwala and its associated health effects. To achieve this, primary data was gathered through a questionnaire survey focused on health issues faced by elderly individuals during the smog season. The results of the survey revealed that older adults in Gujranwala are particularly vulnerable to a range of health problems during this period, including coughing, throat infections, irritated eyes, runny noses, shortness of breath, chest pain while breathing, wheezing, asthma, heart problems, and respiratory issues. In order to analyze the spatial distribution of these health concerns, spatial and geo-statistical methods were employed utilizing ArcGIS 10.5. By integrating field data and secondary sources, hotspot and cold spot zones were identified. Employing the statistical model within ArcMap 10.5, hotspot analysis was performed to determine areas with elevated air quality index (AQI) values and associated health problems. The application of the inverse distance weighted approach, incorporating the Z value, facilitated a visual representation of areas with heightened and reduced AQI and health-related issues. The study's outcomes underscore the prevalence of health challenges among older adults during the winter months in Gujranwala, particularly linked to smog-induced throat infections, irritated eyes, and runny noses. The research identified zones with escalated AQI values, encompassing regions such as Gujranwala, Chandaqella, Alam Chowk, Khali Shahpur, Sialkot Bypass, and Pindi Bypass. It was established that industrial pollutants and vehicular emissions are the primary contributors to smog in the area. Given the detrimental consequences of pollution on individuals of all age groups, it is imperative to take action to mitigate its impact. This can be achieved through addressing pollution sources, implementing effective emission control measures, and fostering public awareness. By adopting proactive measures, the adverse health effects of pollution can be minimized, thereby fostering a healthier and safer environment for the entire population. This study offers valuable insights for policymakers and environmentalists to implement targeted interventions and improve air quality, ultimately safeguarding the health of local populations.

CO2 synergistic emission reduction and health benefits of PM2.5 reaching WHO-III level in Pearl River Delta

Protecting human health is one of the fundamental goals of continuous air quality improvement. Considering the same sources of CO2 and air pollutants emissions, their emission control measures often have a certain degree of synergistic emission reduction effects To balance the costs and policy efficiency, policy makers should assess the synergistic benefits of CO2 emission reduction when formulating air quality improvement strategies. Aimed at the air quality improvement strategy targeting WHO-III level (i.e. 15 μg/m3) for PM2.5 in the Pearl River Delta (PRD) region, this study evaluates the synergistic CO2 reduction effects and the associated health benefits from this strategy which includes a range of air pollution prevention and control measures. The results of the study show that promoting the attainment of WHO-III for PM2.5 in the PRD region can bring about 74 Mt of synergistic CO2 emission reduction, resulting in an 18% reduction of CO2 emissions in the PRD compared to 2017. Among various measures considered, industrial restructuring, power supply transition and industrial energy consumption transformation exhibit the most pronounced synergistic effects. Therefore, these measures are recommended to be prioritized and promoted in the next stage of air pollution prevention and CO2 emission reduction. Furthermore, when the PM2.5 concentration in the PRD region reaches the WHO-III level, the number of PM2.5-related deaths will be estimated to reduce approximately 5.5 thousand compared to that in the current policy scenario. Through continuous structural transformation and emission reduction efforts, it not only facilitates the decline in regional PM2.5 concentration but also helps more regional residents to live in an environment with a relatively low PM2.5 concentration. In addition, in order to reduce the health impacts of PM2.5, it is recommended that the government should guide people to change their production and living styles in order to reduce pollutant emissions from anthropogenic activities.

Investigation of Emission Inventory for Non-Road Mobile Machinery in Shandong Province: An Analysis Grounded in Real-World Activity Levels

In tandem with the advancement of urban intelligent technology, the construction of remote monitoring platforms and databases for non-road mobile machinery is gradually improving in various provinces and cities. Employing the remote monitoring platform for non-road mobile machinery enables a detailed big data analysis of the actual operational state of the machinery. This method yields precise data on the activity levels of various machinery types. Importantly, it addresses the issue of reduced accuracy in emission inventories, which often arises from the conventional practice of using standard recommended values from the Guide to determine machinery activity levels during the compilation of non-road mobile machinery emission inventories. Based on the remote monitoring and management system of non-road mobile machinery, the actual value of the activity level of non-road mobile machinery was obtained, and the emission inventory of non-road mobile machinery in Shandong Province was established. The emission levels of PM, HC, NOx, and CO from main non-road mobile machinery, including forklifts, excavators, loaders, off-road trucks, and road rollers, were measured. The findings indicate that the operational activity levels of non-road mobile machinery in Shandong Province typically exceeded the guideline’s recommended values. Among them, the annual use time of port terminal ground handling equipment was the longest, with an average annual working time of 4321.5 h per equipment, more than six times the recommended value. Among all types of non-road mobile machinery, loader emissions accounted for the highest proportion, reaching 43.13% of the total emissions of various pollutants. With the tightening of the national standard for non-road mobile machinery from Stage II to Stage III, a significant reduction in actual mechanical emissions was observed, primarily manifested as a 91% decrease in NOx emissions. Based on the data from the remote monitoring platform, a new method for compiling the emission inventory of non-road mobile machinery is proposed in this paper. The calculated emission inventory can reflect more real emission situations and provide a reference and basis for emission control and sustainable emission reduction policy measures for non-road mobile machinery.