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Tracking fugitives is an essential part of criminal investigations. When a fugitive is actively evading arrest, moving and hiding to escape, several issues arise. Technological advancements have greatly helped tracking individuals, yet still suspects are able to avoid arrest, sometimes for long periods of time. The current case study provides a review of an infamous fugitive case with modern decision-making analyses. The aim is to show how investigators can return to traditional investigative methods in situations wherein technology is lacking or ineffective. The outcome of the case study review shows the potential to track a fugitive's behavior. It is suggested that this approach can be trialed and tested across other cold or historic cases to further improve the analyses. These desktop scenario sessions can provide effective training for real-time, current fugitive cases.
Popular conventional biogas plants in India are reactors operated on cattle dung slurry and cannot accommodate solid biomass. The study elucidates the performance of a digestion system for solid discarded vegetable (DV), subjecting it to aerobic composting and utilising the derived leachate as feedstock for biomethanation, and also accounts for the fugitive greenhouse gases (GHGs) loss from the system. Leachates from the composting substrates had a BOD5 of 15,305.6 ± 845.1 mg L-1, which was reduced to 912.3 ± 94.0 mg L-1 post-biomethanation. The loss of GHGs was highest in the slurry pit (199.33 ± 14.88 g day-1 CH4 and 315.25 ± 24.59 g day-1) and least from the outlet pipe (0.47 ± 0.03 g day-1 CH4 and 0.74 ± 0.05 g day-1 CO2). Organic leachates from composting DV can be suitably used as substrates for biomethanation. However, attention is needed to minimise the fugitive GHGs loss from the system equivalent to ~2.4 kg CO2e for producing 1.0 m3 of biogas.
Volatile organic compound (VOC) emissions from industrial parks are a crucial source of urban air pollution. This study assessed VOC emissions and their impact on secondary pollution from three key industries-packaging and printing, pharmaceutical manufacturing, and furniture manufacturing-in a typical industrial park in the Guanzhong region of China. The results revealed considerable variation in organized outlet VOC concentrations between the different industries, with the highest level observed in furniture manufacturing (3449.9 ± 437.6 µg/m3) and the lowest level discovered for pharmaceutical manufacturing (410.9 ± 205.5 μg/m3). The VOCs were mainly aromatics (40.7%) and alkanes (21.8%), with pentane, isopentane, xylene, and ethylbenzene the most abundant species. Although organized emissions (1151.6 t/y) constituted the primary source of emissions, fugitive emissions (358.1 t/y) remained a major contributor and primarily contributed aromatics and alkanes. Critically, reactivity-based assessment demonstrated that alkenes and aromatics were the principal contributors to the ozone formation potential (>80%). With regard to the secondary organic aerosol formation potential, aromatics were overwhelmingly dominant, accounting for approximately 87% of the total potential, with xylene and ethylbenzene in furniture manufacturing alone contributing 72.9%. The findings highlight the importance of prioritizing controls on highly reactive alkenes and aromatics. Fugitive emission management during storage, mixing, and curing stages should be enhanced and solvents should be substituted to effectively control VOC emissions in industrial parks.
Soil fugitive dust significantly degrades air quality in arid regions like Bole City, China. To address methodological limitations causing Particulate matter (PM) overestimation, this study aimed to: (a) Develop a refined 2021 inventory for PM10 and PM2.5 soil dust emissions in Bole City by integrating localized particle size data and the critical TSP proportion coefficient; (b) Analyze emission spatial patterns; and (c) Assess sensitivity to climate parameters. Methods were used to combine on-site sampling, localized coefficients, the TSP coefficient, meteorological data, and remote sensing. Results showed annual emissions of 422.60 t PM10 and 166.91 t PM2.5. Grassland was the dominant source 153.03 t PM10 and 58.67 t PM2.5, while bare land contributed least 2.39 t PM10 and 1.05 t PM2.5. Emission intensities were 0.07 t/km2 PM10 and 0.03 t/km2 PM2.5. Emissions peaked sharply in April (214.70 t PM10; 66.55 t PM2.5) and were lowest in May (2.82 t PM10; 2.16 t PM2.5). Spatially, emissions were low northeast and high southwest. Precipitation was the most sensitive climate factor, followed by temperature and wind speed. In conclusion, this study provides Bole City's first localized inventory incorporating the TSP coefficient, correcting prior overestimation. It identifies grassland as the key source, highlights April's peak emissions and the distinct southwest-increasing spatial pattern, and demonstrates precipitation's paramount sensitivity. These findings offer a crucial quantitative basis for targeted soil fugitive dust control strategies in Bole City and similar arid zones. The study examines soil fugitive dust pollution in Bole City, near Sayram Lake, located in the Xinjiang Uygur Autonomous Region, China. Fugitive dust, particularly particulate matter (PM10 and PM2.5), affects air quality and human health. By using data from 2021, the study calculated the total emissions of PM10 and PM2.5 based on field samples, meteorological data, and localized coefficients. We found that emissions were highest in April, due to dry conditions and strong winds, and lowest in May when vegetation cover increased. Grasslands contributed the most to emissions, followed by rocky terrains, while bare lands contributed the least. Spatially, emissions were higher in the southwest and lower in the northeast of the city. A sensitivity analysis revealed that precipitation had the strongest influence on dust emissions, followed by temperature, with wind speed having a lesser effect. This research provides important data to help manage and reduce soil dust pollution in Bole City.
Accurate monitoring and quantification of methane (CH4) emissions from water resource recovery facilities (WRRFs) are essential for regulatory compliance, process optimization, and the development of effective greenhouse gas (GHG) mitigation strategies. A few previous studies applied individual CH4 sensing methods (e.g., ground sensors or satellite imaging) to quantify CH4 emissions from wastewater treatment and biogas facilities. However, the complementary benefits of integrating multiple approaches for WRRF emissions monitoring have not been evaluated. In the current study, sixteen ground sensors were strategically distributed and installed in a Canadian WRRF to capture the spatial and temporal variabilities of CH4 concentrations emitted from various treatment processes within the plant. In addition, a one-week on-site campaign was conducted using a handheld optical gas imaging (OGI) camera and drone-based sensors to isolate CH4 emissions from different treatment processes. The average CH4 emissions from the WRRF were determined to be 4.0 ± 2.5 g-CH4/m3 of treated wastewater, representing 3.2 - 3.5% of the influent COD load to the facility. Interestingly, the on-site campaigns revealed that approximately 63% of the plant's total CH4 emissions originated from aeration basins and primary tanks. Moreover, it was found that OGI and drone-based measurements are complementary. Drone-based measurements were effective in covering large areas and detecting dispersed emissions while the OGI camera was valuable for detecting localized emissions in areas with stagnant airflow. This study demonstrates the value of integrating multiple sensing approaches for comprehensive CH4 monitoring and reveals valuable insights into emission hotspots, enabling more targeted and effective mitigation strategies.
Household air pollution (HAP) associated with solid fuel use is one major environmental factor contributing to adverse human outcomes. Although outdoor air quality influences indoor environments, severe HAP is closely and directly affected by indoor smoke leakages. However, the influences of fuel-stove characteristics and user operational behaviors on this process remain poorly understood. In this study, a suite of laboratory-controlled experiments was conducted to systematically elucidate the effects of fuel-stove characteristics and operator behaviors on smoke leakages during indoor biomass combustion. Pelletized fuels exhibited the lowest leakage fractions under the tested conditions, suggesting a better fuel-stove compatibility in terms of leakage control. Increasing chimney height from 1 m to 3 m reduced the leakage fraction of PM2.5 from 43 ± 8% to 17 ± 4%, and that of CO from 21% to 14%. User operational behaviors importantly influenced smoke leakage as closing the ash outlet reduced leakage fractions by about 24-85%, while a rapid fuel feeding increased the leakage. A generally positive correlation was observed among pollutants, however, the magnitude and dynamics of leakage differed by species. CO showed significantly lower leakage fractions than particles, and low molecular weight volatile organic compounds generally leaked less than high molecular weight species. These results indicate that leakage is strongly affected by both fuel-stove compatibility and user operation, and that assuming identical leakage fractions across pollutants may oversimplify exposure assessment and emission modeling.
This study quantified toxic metal concentrations in settled atmospheric dust in the vicinity of cement storage facilities and evaluated associated human health risks in selected Nigerian cities. Dust samples (n = 75) were collected from five active cement depots across Ondo State and Abuja and analyzed for 37 elements using inductively coupled plasma optical emission spectrometry. Human health risks for adults and children were assessed through ingestion, inhalation and dermal exposure pathways following United States Environmental Protection Agency models as a screening-level assessment. Lead concentrations were highest at Igodan Lisa, Okitipupa (726.5 mg/kg), approximately fourteen times higher than levels measured at the lowest site (Weye Police Station, Abuja). Total hazard indices exceeded the safe threshold of 1.0 by over two orders of magnitude for both adults (HI = 137.5) and children (HI = 58.9), indicating substantial non-carcinogenic risk. Inhalation exposure dominated overall risk, accounting for more than 99 % of the average daily dose for chromium, lead and nickel. Estimated cancer risk for children via chromium inhalation reached 5.1 × 10⁻³ , equivalent to one additional cancer case per two hundred exposed individuals and far above the acceptable benchmark of 1 × 10⁻⁶. Principal component analysis suggested mixed industrial and crustal sources, although source attribution remains inferential due to the absence of airborne particulate matter measurements and mineralogical confirmation. These findings identify areas surrounding cement storage facilities as hyper-localized hotspots of toxic metal exposure, though conclusions are constrained by dry-season sampling and reliance on total rather than bioaccessible metal concentrations.
The iron and steel industry is a major PM emitter. Using data from 99 Chinese sites, an LMDI model is applied to decompose PM emission changes into five process‑specific factors: steel output, energy consumption intensity, waste gas generation coefficient, stack emission concentration, and fugitive emission factor, separating stack from fugitive emissions. Nationally, PM emissions declined 23.6% from 2011-2016. The steel output effect drove an 83.7% increase in 2010-2011 but became a reduction driver after 2014. The waste gas generation coefficient effect consistently increased PM emissions (19,516 t in 2015-2016). The stack concentration effect was the dominant inhibitor (reduction up to - 31,558 t in 2015-2016). The fugitive emission factor effect shifted from positive (5,037 t in 2010-2011) to strongly negative (- 23,320 t in 2015-2016). Energy intensity effects were small (<25% contribution). Regional analysis reveals heterogeneity. Most regions followed the national trend, but South China and Northwest China showed annual PM increases, with positive stack emission concentration and fugitive emission factor effects. In Northwest China, the total effect was positive in five of six years, ranging from 1,408 t to 8,305 t annually, with fugitive emissions contributing up to 232% of the annual change. These findings imply that uniform national policies are insufficient. Targeted interventions of accelerating dust removal deployment in South/Northwest China and strengthening fugitive controls was proposed.Implications: The iron and steel industry remains a critical contributor to particulate matter (PM) emissions, with significant implications for air quality, public health, and climate policy. This study identifies and quantifies the key drivers of PM emissions across China's steel-producing regions, providing a nuanced foundation for targeted emission-reduction strategies. The findings underscore that while national PM emissions have declined overall - driven largely by improved stack emission controls and fugitive emission management - regional disparities persist, particularly in Northwest and South China where certain factors continue to promote emission increases. These insights emphasize the need for regionally tailored policies that address local industrial practices, energy structures, and enforcement capacities. By prioritizing technological upgrades in dust removal, fugitive emission containment, and energy efficiency, policymakers and industry managers can better align steel production growth with air quality and health protection goals. Furthermore, this analysis supports China's broader efforts to achieve "blue sky" objectives and transition toward greener industrial development, offering a replicable framework for other heavy industrial sectors and regions grappling with similar pollution challenges. Ultimately, integrating such evidence-based driver analyses into environmental governance can enhance the effectiveness of PM mitigation, reduce health burdens on vulnerable populations, and promote sustainable industrial transformation in the face of ongoing economic and climatic pressures.
Copper smelting is an important source of unintentional persistent organic pollutants (POPs). Yet emission assessment and inventories remain limited by two key field-evidence gaps: (i) scarce measurement-based emission factors (EFs) for primary copper smelting and (ii) a lack of quantitative constraints on fugitive-derived POP releases. In this study, we conduct field measurements at three primary copper smelting plants and compare POP burdens across end-of-pipe stack gas and a secondary-capture stream capturing fugitive-derived gas. For primary copper smelting using an Ausmelt furnace with electrostatic precipitation as the end-of-pipe control, EFs of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), dioxin-like polychlorinated biphenyls, and polybrominated dibenzo-p-dioxins and dibenzofurans were estimated at 0.03-0.14, 0.004-0.023, and 0.055-0.062 μg TEQ t⁻1, respectively. In contrast, reported PCDD/F EFs could be as high as 0.65 μg TEQ t⁻1 for oxygen-enriched side-blown furnace smelting equipped with baghouse filtration. These results indicate that emissions from primary copper smelting warrant attention in regions with concentrated production activity. The secondary-capture stream exhibited comparable POP concentrations to those in end-of-pipe emissions. Fugitive-related pathways could contribute emissions on the same order as end-of-pipe releases. Fugitive releases should be explicitly considered to reduce systematic underestimation in inventories and associated risk assessments.
Wood furniture manufacturing is a solvent-intensive industry with significant volatile organic compounds (VOCs) emissions. Six wood furniture manufacturing enterprises in Shandong Province were selected to determine the VOCs emission characteristics of the industrial sector. The fugitive emissions from the drying workshop were not captured or vented through a controlled exhaust system, resulting in the highest total VOCs (ΣVOCs) concentration (18.06 mg/m3), while the sizing workshop had the lowest concentration. Halogenated hydrocarbons and oxygenated VOCs were the main components of the fugitive emissions. In areas with emission controls, spliced exhaust and sizing exhaust had the lowest ΣVOCs concentration, while primer exhaust and surface coating exhaust had high ΣVOCs concentrations. Aromatics contributed significantly to the ozone formation potential and secondary organic aerosol production potential in areas with fugitive and organized emissions. The main species were m-p-xylene, m-xylene, and p-diethylbenzene. A carcinogenic risk was posed by 1,2-dichloroethane in the primer and drying workshops. The UV roller coating workshop presented the highest non-carcinogenic risk, with the main contributor being 1,1,2-trichloroethane. Its hazard quotient of 714 was much higher than the critical value of 1 set by the US EPA standard. Future VOC management measures were proposed for the wood furniture manufacturing industry. The results provide extensive data support for VOC pollution control and the management of occupational health risks in the wood furniture manufacturing industry in Shandong Province.
Understanding greenhouse gas (GHG) emissions from natural gas systems is essential for transitioning to a low-carbon economy. This work estimates well-through-transmission GHG emissions of the US natural gas from one million wells covering 91% production in 2023. A high-resolution US oil and gas production area map is developed to harmonize spatial and tabular data from the oil and natural gas (O&NG) supply chain. We systematically integrate latest aerial campaign measurement into natural gas life cycle GHG emission estimates, capturing methane fugitives with better characterization of superemitter events. More than ten public and commercial data sets are integrated with an engineering-based unit process life cycle assessment (LCA) model. The estimated total GHG emissions from the US gas sector are 719 MMT CO2eq, more than twice the estimates of the US Environmental Protection Agency. The average well-through-transmission carbon intensity (CI) for US natural gas is 15.99 [15.14, 16.90] gCO2eq/MJ, with an upstream (exploration through processing) CI of 12.27 [11.84, 12.68] gCO2eq/MJ and a midstream (transmission) CI of 3.72 [3.30, 4.22] gCO2eq/MJ (bracketed values indicate uncertainty ranges). Methane fugitive and venting account for 61% and 21% of the upstream CI, an order of magnitude higher than flaring contributions (2.1%). Reducing methane fugitive and venting loss rates by 75% would reduce the upstream CI by half.
Brewing is an understudied but influential source of VOC emissions in the food manufacturing industry. In this study, we conducted a first comprehensive analysis of process-based VOC concentration characteristics, ozone formation potential (OFP), secondary organic aerosol formation potential (SOAFP) and health risks in two typical breweries in Beijing that use malted barley, hops, water, and yeast. In Brewery A, 35 to 53 distinct VOC species were detected, with total mass concentrations ranging from 148.17 ± 18.64 µg m-3 to 15 225.91 ± 1912.51 µg m-3. Brewery B demonstrated comparable patterns, with 28 to 49 species detected at concentrations between 104.49 ± 8.48 µg m-3 and 10 368.87 ± 879.47 µg m-3. Process-stage analysis identified boiling and fermentation stages as the key stages with the highest VOC concentrations, dominated by oxygenated VOCs (OVOCs) such as acetaldehyde, acetone, ethyl acetate, and 2-butanone, as well as the alkane isobutane. Atmospheric dispersion modeling (AERMOD) indicated negligible public health risks from organized stack emissions. In contrast, occupational health assessment revealed significant risks for workers from fugitive emissions, with the cumulative hazard index (HI) far exceeding the threshold. The OFP and SOAFP results, representing the secondary pollutant formation potential of the source mixtures, highlighted OVOCs and aromatics as priority control species for mitigating the secondary pollution potential. The findings demonstrate that VOC control strategies must be differentiated, with large-scale breweries prioritizing organized emissions, while small breweries urgently need to control fugitive emissions. This study aims to promote the implementation of VOC regulations and occupational health protection strategies within the brewing industry.
Volatile organic compounds (VOCs) are critical precursors of secondary air pollution and pose substantial occupational health threats. This study established an integrated analytical framework to characterize VOCs at a large rubber manufacturing plant in central China, covering unorganized fugitive emissions and organized stack emissions at the inlet and outlet of air pollution control devices (APCDs). Total VOC concentrations (TVOC), chemical profiles, ozone formation potential (OFP), and health risks of hazardous air pollutants (HAPs) were quantified together with compound-specific APCD removal efficiencies. Results showed strong process-dependent emission characteristics. Total VOC (TVOC) concentrations at stack outlets reached 27225 ± 1997 μg/m3 and 13323 ± 1626 μg/m3 for rubber refining and vulcanization, respectively. Alkanes dominated fugitive emissions, whereas halocarbons (50-61%) were dominant in stack emissions, with methylene chloride as the most abundant species. Both processes contributed significantly to regional ozone formation, with aromatics accounting for 37-49% of total OFP. Notably, the vulcanization APCD achieved a much higher VOC removal efficiency (73%) than the refining unit (36%). However, current APCDs exhibited strongly selective removal performance: poor or inefficient removal for high-risk species in rubber refining, and unstable styrene removal in vulcanization. Health risk assessment revealed an obvious spatial gradient in HAP concentrations (stack inlet > stack outlet > plant area > operating area), with extreme carcinogenic and non-carcinogenic risks identified at the stack outlets. This study identifies key limitations of existing end-of-pipe control technologies and supports the development of targeted, cleaner production strategies for the rubber industry.
As a crucial component of bioaerosols, proteinaceous matter (PrM) significantly impacts on the physical and chemical properties of aerosols, regional and global climate, and human health. In this study, the seasonal variation and sources of PrM in Xi'an were analyzed. The protein and free amino acids (FAAs) concentrations were the highest in winter while for combined amino acids (CAAs) were in autumn, and they all had the lowest level in summer. The CAAs/FAAs ratios ranged from 5.9 (winter) to 11.7 (autumn), indicating the important contribution of local emissions to PrM. It was noted that hydrophobic amino acids species were predominant in both FAAs (47 %) and CAAs (62.8 %). Phenylalanine (FAAs: 23.6 %; CAAs: 38.9 %), lysine (FAAs: 13.7 %; CAAs: 23.8 %), and valine (FAAs: 9.9 %; CAAs: 20.4 %) dominated in amino acids. The correlations analysis indicated that atmospheric oxidation processes of CAAs could be an important formation for FAAs in spring and summer. Source apportionment identified that remote transportation (33.1 %), coal/biomass burning (23.6 %), plant emissions (20.3 %), and secondary formation (16.5 %) were the major sources for FAAs, while plant emissions (49.3 %), fugitive dust (24.9 %), and remote transportation (18.6 %) were the major sources for CAAs. This study highlighted combustion sources and atmospheric chemical reaction process were important formation for FAAs, while nature process dominated the CAAs sources. Such results help to understand the bioaerosol profiles and formation, and further to make control measurements in future.
In China, the intensive supervision mechanism (ISM) has been implemented to combat air pollution, yet its effectiveness remains under debate. This study systematically evaluated the effectiveness of the ISM using a multisource data set integrating the CHAP data set, meteorological factors, and ISM data, with the iron and steel industry as a case study. The results indicated that the number of issues identified and the number of enterprises involved from 2018 to 2024 exhibited spatiotemporal heterogeneity. The environmental issues identified by ISM data across different processes were grouped into three main categories: automatic monitoring of pollution sources and data management, pollutant emission control and compliance, and fugitive dust and particulate matter control. Linear regression model revealed that ISM contributed to air quality improvements, influenced by baseline pollutant concentrations, meteorological factors, and the implementation intensity of the ISM. Provincial-level spatial autocorrelation indicated positive clustering between ISM implementation intensity and reductions in pollutant concentrations, particularly in Hebei, Henan, Shanxi, and Shandong Provinces. Enterprise-level evaluation revealed that even in regions with overall strong performance, significant heterogeneity existed among individual enterprises, highlighting the need for refined enterprise-level assessment and differentiated management. These findings underscored ISM's tangible effectiveness and provided empirical support for its long-term optimization.
The waste sector is the third-largest anthropogenic source of methane emissions, significantly contributing to the greenhouse effect. Accurate quantification of landfill methane emissions is essential for effective waste management and emission reduction policies. However, current regional inventory-based assessments often overlook site-specific heterogeneity, while emerging satellite observations remain temporally sparse. This study provides a nationwide, site-level characterization and quantification of methane emissions from MSW landfills in China by integrating bottom-up inventory estimates with hyperspectral satellite observations. We first developed a comprehensive database containing site-specific information for more than 300 major MSW landfills to analyze their spatial and temporal distribution patterns. Methane emissions from individual landfills were then estimated using the IPCC first-order decay method, revealing an increase from 1.015 Mt in 2005 to a peak of 2.161 Mt around 2015, followed by a decline to 1.98 Mt in 2023. We further compared these inventory results with hyperspectral satellite observations (EMIT, PRISMA) for three typical landfill sites. The comparison revealed that satellite-detected instantaneous emissions consistently exceed inventory-based averages, quantifying a systematic bias in current IPCC models which tend to underestimate fugitive leaks. Uncertainty in the results primarily arises from parameter assumptions in inventory models and wind-related variability in satellite-based flux inversion. Finally, a scenario analysis projects that the full implementation of China's "Zero Waste" policy could reduce landfill methane emissions by approximately 59 % by 2030. Our findings highlight the importance of combining bottom-up inventories with top-down satellite monitoring for improved landfill management and provide valuable insights for national carbon mitigation strategies.
Species bounty programs, much like bounty hunters charged to bring fugitives to justice, enlist the public to locate and remove unwanted species through financial incentives. With the goal of reducing population sizes, these programs address perceived ecological and economic damage caused by target species. In this study, we provide the first global assessment of species bounty programs, drawing on evidence from both historical and contemporary efforts across diverse regions and cultural contexts over the past eight centuries. We uncovered a long history of bounty programs involving at least 283 species-mammals, birds, fish, plants, reptiles, mollusks, insects, amphibians, and crustaceans-across 449 programs in 60 countries. Using this collective knowledge, we offer five perspectives on species bounty programs. First, bounty programs are launched for a variety of reasons, including economic (livestock, crops, fisheries, infrastructure), ecological (species, ecosystems), and social (human health) considerations related to unwanted species. Second, bounty programs vary in their design and implementation, ranging from well-planned operations with clear management and conservation objectives to ad hoc operations with limited articulation and investigation of project outcomes. Third, evidence points to unintended consequences, in which bounty programs result in the incidental removal of non-target species or in effects that may inadvertently benefit target species. Fourth, while not always the case, fraudulent activities have been reported, compromising the management outcomes of some programs. Fifth, public perception of bounty programs is highly dynamic and ensuring program engagement remains a persistent challenge. By reviewing the scattered narratives of past and present bounty programs globally, this review seeks to inform the evolving role of this management strategy.
The COVID-19 pandemic led to three years (2020-2022) of human activity restrictions in China, significantly impacting urban air quality, yet long-term health risks from PM2.5-bound heavy metals remain unclear. This study observed PM2.5 and 21 associated metals in Shenzhen over six years (2017-2022), aiming to identify sources, assess their health impacts, and explore COVID-19 effects on health risks. The total carcinogenic risk (CR) of 5 metals decreased by 23 % during the pandemic (2020-2022) compared to pre-pandemic levels (2017-2019), similar to the trends of PM2.5 and total metals concentrations. In contrast, the non-carcinogenic risk (NCR) of 11 metals increased by 20 %, primarily due to the rise in manganese (Mn) concentration caused by vehicle emissions, but NCR still below the risk threshold. Vehicle emissions were the main contributor to NCR (68 %) and CR (55 %). Machine learning revealed that the source emissions reduction is the primary factor contributing to the decline in the CR of metals bound to PM2.5, except for the increased health risk associated with vehicles. During the pandemic, the slowed growth rate of CR of vehicle emissions and the significant decline in CR of fugitive dust demonstrated the effectiveness of pandemic-induced traffic and production restrictions in reducing anthropogenic emissions and mitigating PM2.5-bound heavy metal health risks in Shenzhen. However, total CR of heavy metals in 2022 exceeded the acceptable risk threshold (1 × 10-6), emphasizing the ongoing challenge of regulating PM2.5 and the need to prioritize vehicle emission management.
Pesticide manufacturing is a significant source of volatile organic compounds (VOCs), contributing to secondary pollution, climate impacts, and human health risks. However, a lack of process-resolved measurements, reliable emission factors (EFs), and integrated impact assessments limits effective emission control in this sector. Here, full-process measurements of 110 VOC species were conducted in two representative pesticide manufacturing enterprises in China. EFs for 18 pesticide products (10.42-329.73 kg/t) and four emission sources (14-104.65 kg/t) were firstly developed. An emission-weighted method was developed to establish source profiles, revealing that aromatics (38%), OVOCs (21%), and halocarbons (20%) were dominant species. Toluene, dichloromethane, acetone, acetaldehyde, and, chloroform are key contributors. Based on updated EFs, a province-level VOC emission inventory for 2024 was constructed (516.61 Gg), with over 60% of emissions concentrated in four provinces. Without additional controls, emissions are projected to increase to 664.19 Gg in 2030 and 838.37 Gg in 2035. Scenario analysis indicates that fugitive emission control is the most effective single measure, while region-specific strategies can further enhance mitigation efficiency. A multi-metric assessment framework was established to integrate VOC emissions, ozone formation potential (OFP), secondary organic aerosol formation potential (SOAP), ozone depletion potential (ODP), and global warming potential (GWP). It could reveal substantial heterogeneity in mitigation performance. It is shown that "Process control" achieved the highest synergistic benefits, reducing total emission, OFP, SOAP, ODP, and GWP by 36%, 29%, 55%, 53%, and 66%, respectively. These findings provide a robust scientific basis for process-oriented VOC management and targeted mitigation strategies in pesticide manufacturing.
This study presents a facility-wide assessment of greenhouse gas (CH₄, N₂O, CO₂) and air-pollutant (NH₃, H₂S, NMVOC) emissions from a tertiary municipal wastewater treatment plant in northern California. Emissions were quantified using complementary unmanned-aerial-vehicle (UAV) flux-curtain, dynamic flux-chamber, and source-testing approaches across four campaigns. The UAV method provided spatially integrated, top-down CH₄ fluxes, while chambers and source tests captured spatiotemporal variability of multiple gases from individual processes. The highest UAV flux (26.4 ± 6.3 kg CH₄ h⁻¹) in the first campaign coincided with a fugitive digester leak detected and later repaired, demonstrating UAV sensitivity to large, transient CH₄ releases. Across the remaining campaigns, mean UAV-derived facility-wide emissions were 1.44 kg CH₄ h⁻¹, approximately 90 % lower than the ∼13.3 kg CH₄ h⁻¹ mean facility-wide emissions estimated from summed flux chamber and point-source measurements. Total operational-carbon emissions, integrating direct and indirect forcing contributions, were 12,000 ± 500 Mg CO₂-eq yr⁻¹ (1.80 ± 0.07 kg CO₂-eq m⁻³ wastewater). The candlestick flare and biosolids drying operations accounted for 86 % and 14 % of total CH₄ emissions, while secondary treatment dominated CO₂, NH₃, and N₂O generation. Emission variability was governed primarily by unit process, followed by time of year (e.g., wet or dry season) and time of day, with higher fluxes during dry-season daytime conditions. The integrated UAV, chamber, and source testing framework established herein provides a novel, multi-scale approach for quantifying and mitigating facility-wide GHG and air-pollutant emissions. The methodology and mechanistic insights are transferable to wastewater utilities globally, supporting data-driven, low-carbon treatment design and operation.