Emissions Of Various Pollutants Research Articles

Emission reduction effect of low-carbon power generation and heating systems in industrial areas based on collaborative benefit evaluation

To predict the future emission trends of various pollutants, a greenhouse gas calculation system is studied and the emissions of various pollutants are calculated. Then, an energy-saving supply curve is used to evaluate the economic feasibility of a certain technology. In addition, this study also utilises a synergistic effect analysis strategy and designs emission reduction target scenarios for 2030 based on spatial regression. These scenarios include energy structure adjustment, energy efficiency improvement, waste heat recovery, and end-of-life governance. The results showed that in the next decade, the emissions of CO2, NOx, CO, SO2, PM10, PM2.5, VOCs, and NH3 in industrial parks would continue to increase. The emission of CO2 was expected to reach 289,866,000 tons. Under the four emission reduction goals, the ‘energy efficiency improvement’ scenario had the most significant reduction effect on greenhouse gases and atmospheric pollutants, with CO2 emissions reduced by 103,251,000 tons and atmospheric pollutants reduced by 16,900 tons. This study suggests that industrial parks choose the most suitable emission reduction strategy based on the advantages of each emission reduction target scenario, in order to achieve better environmental effects.

Comparative Experimental Assessment of Pollutant Emission Behavior in Combustion of Untreated and Thermally Treated Solid Biofuels from Spruce Chips and Rapeseed Straw

Biomass energy for heating is going to be part of the spectrum of renewable energy sources. However, biomass combustion produces emissions of various pollutants with negative effects at both local and global scales. To reduce some of the locally important pollutant load, thermally treated biomass fuels may offer a partial solution. In this study, two biomass feedstocks, i.e., spruce chips and rapeseed straw, were thermally treated at 300 °C to produce biochars. Subsequently, both original materials and biochars were burned in a 25 kW retort combustion device. In both cases, the biochar showed lower emissions of carbon monoxide and nitrogen oxides, usually almost across the whole range of tested combustion conditions. In total, for the emission production per unit of net calorific value, the spruce biochar showed reductions in CO and NOx productions of 10.8% and 14.5%, respectively. More importantly, in rapeseed straw biochar, the difference was more pronounced. The total production was reduced by 28% and 42%, again in CO and NOx emissions, respectively.

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.

Multi-Objective Experimental Combustor Development Using Surrogate Model-Based Optimization

Abstract The majority of premixed industrial gas turbine combustion systems feature two or more separately controlled fuel lines. Every additional fuel line improves the operational flexibility but increases the complexity of the system. When designing such a system, the goals are low emissions of various pollutants and avoiding lean blowout or extinction. Typically, these limitations become critical under different load conditions of the machines. Therefore, it is particularly challenging to develop combustors for stable and clean combustion over a wide operating range. In this study, we apply the Gaussian process regression machine learning method for application to burner development, with the aim of improving the process, which is often driven by a trial-and-error approach. To do so, a special pilot unit is installed into a full-scale industrial swirl combustor. The pilot features 61 positions of fuel injection, each of which is equipped with an individual valve, allowing to modify the fuel–air mixture close to the flame root in various degrees. In fully automatized atmospheric tests, we use the pilot system to train two surrogate models for different design objectives of the combustor, relevant for full load and part load operation, respectively. Once trained, the models allow for prediction for any possible injection scheme. In combination, they can be used to identify pilot injector configurations with an improved operation range in terms of low NOx emissions and part load stability. The adopted multimodel approach enables combustor design specifically for high operational flexibility of gas turbines, but can also be extended to other similar industrial development processes.

Atmospheric dristribution of traffic heavy metals at temu-interchange, Epe Lagos, Nigeria

The Atmospheric distribution of traffic heavy metals is a dynamic process that involves the emission of various pollutants released from vehicular traffic. It has affected both human and plants around Temu-interchange hence, the need to characterized the emissions. The objective of the study was determined concentration of Particulate Matter (PM) and Enrichment Factor (EF) depending on the traffic emission. The research was conducted using deposition method. The study area and the control experiment were conducted simultaneously for a period of thirty (30) days between December 2022-January 2023 (Dry Season). Samples were prepared and deposition fluxes (DF) were determined. The particulates were taken to the Central Research Laboratory, Tanke in Ilorin for characterization using X-ray Fluorescence (XRF) spectrometer. EF was also determined. Thirteen elements Fe, Ag, Cd, Zn, Sn, Ti, In, Co, Mn, Pd, Rh and Ru were characterized from the samples collected at the study area while Twenty-one Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ge, As, Zr, Sr, Pb, W, Po and Ac elements were characterized from the samples collected at the control unit of the experiment. The EF of the detected elements both in the study area and in the control, experiment was determined. Five elements in the study area were moderately enriched, while elements such as S, Cl and Zn were highly enriched in the control unit. An indication of anthropogenic activities particularly traffic emission influence within the area hence, a clean-up of the study area is highly recommended.

Effect of thermal treatment on zeolite for real-time gas sensing of oxygenated volatile organic compounds

The breathable air is severally polluted due to the emission of various pollutants like volatile organic compounds (VOCs) and dust particles of submicron sizes. These pollutants have several adverse health hazards, which can cause fatal accidents and mortalities. In the current study, we have modified the FAU type of Zeolite (ZE) with the Si/Al to 1 and treated at different temperatures (300–600 °C) in a 10% H2 + 90% N2 mixture to achieve different distributions of oxygen vacancies. The presence of oxygen vacancy and electrons in the lattice is confirmed by EDAX, XPS and ESR techniques. The charge irregularities generated due to trapped electrons are exploited for detection of different VOCs like acetone, ethyl methyl ketone, isopropyl alcohol, ethanol, n-hexane, and benzene using the scanning kelvin probe (SKP) technique. The oxygen vacancies raise the distribution of Lewis and Brønsted basic sites, which impacts the interaction of VOCs with the sample surface and the amount of VOCs uptake. The untreated ZE and treated at 600 °C (ZE600) exhibited n-type behavior with 13.8% oxygen deficient sites with ∼1.9 μmol/g of total basic sites and 3 μmol/g of total acidic sites. The thermal treatment for ZE600 leads to ∼280 folds enhancement in surface photovoltage towards acetone with ∼ 67% of recovery concerning untreated ZE.

A Quantizing Method for Atmospheric Environment Impact Post-Assessment of Highways Based on Computational Fluid Dynamics Model

The post-assessment of highway atmospheric environmental impacts was limited by the traditional air pollution prediction model, which cannot adapt to complex terrain and complex obstacle scenes. The traditional model has a single evaluation index, which cannot accurately evaluate and predict the transient and long-term emissions of various pollutants. Based on the computational fluid dynamics model, this work establishes a post-assessment method of the atmospheric environment impact of the Beijing–Chengde Expressway construction project. The main pollution factors NOx and CO of highway traffic for transmission and diffusion simulation analysis were selected. The influence law of traffic function, environmental impact, meteorological conditions, and landform on the diffusion of pollution factors in complex tunnel sections were analyzed. It concludes that the pollution within 200 m along the expressway is severe and mainly concentrated in the tunnel entrance and gully area. The NOx concentration is generally higher than CO. The environmental quality is not up to standard and has a diffusion trend with increased traffic flow, operation time, wind speed, wind temperature, and wind direction frequency. The research results can provide theoretical guidance and technical support for the scientific post-assessment of highway environmental impact under complex conditions.

Assessment of the Urban Expansion and Its Impact on the Eco-Environment—A Case Study of Hefei Municipal Area

With the advancement of urbanization, the ecological environmental changes caused by the continuous expansion of cities have become a major concern. Thus, this study is based on a remote sensing image map of Hefei city from 1984 to 2020, which is now in the process of rapid development. We constructed an index system with ecological land, ecosystem service value, ecological environment quality, urban land expansion coefficient, urban heat island rate index, total pollutant emissions, ecological pressure, and ecological deficit, and then evaluated the ecological environment of Hefei city with the help of the entropy weight comprehensive evaluation method. The results show that (1) in the positive evaluation index, the ecological land area was reduced to half of the original area, the ecological service value was reduced by 0.37 times its initial value, and the eco-environmental index was <35 and still decreasing. (2) In the negative evaluation index, the urban heat island ratio index increased by nearly 10 times its initial value, the total emission of various pollutants increased by 6.64 times its initial value, the ecological deficit increased year by year after 1999, and the ecological pressure in 2020 increased to 3 times that in 1999. (3) The overall environmental score of the Hefei urban area has decreased by 48.6 times its initial value. The values of positive evaluation indexes are decreasing, whereas the values of negative evaluation indexes are increasing, and both these items are moving backward, leading to the decrease in the comprehensive ecological environmental score. It can be noticed that the urban expansion of Hefei has had a severe impact on the ecological environment, resulting in the continuous reduction in the ecological land area, a serious urban heat island effect, and continuous weakening of regional ecological service functions. The study results can be used for reference in alleviating the impacts of urban expansion on the environment, promoting the optimization of the urban landscape and the sustainable development of the social economy and environment.

Integrated analysis of energy-pollution-health nexus for sustainable energy planning

In recent years, the emission of various pollutants has caused many problems for human life and the ecosystem. The prioritization between different air pollution control scenarios is a challenge between scientists and policy-makers. This study develops an integrated method for sustainable energy planning considering the energy-pollution-health nexus. The paper investigates three main pollutants (i.e., PM2.5, SO2, and NOx) of different emission sources (i.e., industrial, residential, and intra-city and suburban transportations) in twelve scenarios. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) is applied to model the air pollution dispersion, and Environmental Benefits Mapping and Analysis Program - Community Edition (BenMAP-CE) is used for the health effect assessment. Also, the health and economic benefits of the scenarios are estimated for a region in Qazvin, I. R. Iran. Finally, the trades-off between the health benefits of cleaner ambient air and the economic benefits of energy scenarios are carefully studied for prioritizing the scenarios. The results show the scenarios of thermal efficiency enhancement of gas heaters and converting 30% of gasoline cars to CNG-burning cars in the intra-city transportation sector are the most appropriate scenarios to reduce pollution according to the net profit (about 8 and 6.3 million USD, respectively) while the scenario of reducing 10% of industrial production is the worst scenario according to this criterion (−46.4 million USD). Accordingly, the results emphasize that the closure of industrial plants to control air pollution should be stopped because it has high economic loss while its health benefit is inconsiderable in the region. The framework and results of the present paper are helpful for policy-makers, managers, and authorities to develop sustainable energy planning.

Marble Dust Effect on the Air Quality: An Environmental Assessment Approach

All over the world, increasing anthropogenic activities, industrialization, and urbanization have intensified the emissions of various pollutants that cause air pollution. Marble quarries in Pakistan are abundant and there is a plethora of small- and large-scale industries, including mining and marble-based industries. The air pollution caused by the dust generated in the process of crushing and extracting marble can cause serious problems to the general physiological functions of plants and it affects human life as well. Therefore, the objectives of this study were to assess the air quality of areas with marble factories and areas without marble factories, where the concentration of particulate matter in terms of total suspended particles (TSP) was determined. For this purpose, EPAM-5000 equipment was used to measure the particulate levels. Besides this, a spectrophotometer was used to analyze the presence of PM2.5 and PM10 in the chemical composition of marble dust. It was observed that the TSP concentrations in Darmangi and Malagori areas of Peshawar, Pakistan—having marble factories—were 626 µg/m3 and 5321 µg/m3 respectively. The (PM2.5, PM10) concentration in Darmangi was (189 µg/m3, 520 µg/m3) and in Malagori, it was recorded as (195 µg/m3, 631 µg/m3), which was significantly higher than the non-marble dust areas and also exceeded WHO recommended standards. It was concluded that the areas with the marble factories were more susceptible to air pollution as the concentration of TSP was significantly higher than the recommended TSP levels. It is recommended that marble factories should be shifted away from residential areas along with strict enforcement. People should be instructed to use protective equipment and waste management should be ensured along with control mechanisms to monitor particulate levels.

Then and Now: COVID-19 Pandemic Lockdown Misfire Atmospheric Methane over India

COVID-19 lockdown resulted in the revival of the environment due to reduced emissions of various pollutants globally. In particular, aerosols, NOx and SO2 showed significant reductions at most places. However, the greenhouse gases are not necessarily following this reduction everywhere. In most areas, a decrease in NOx increases methane (CH4) concentration by enhancing the lifetime, but also results in decreased concentrations with reduced emissions. Analyzing the atmospheric CH4 variations during the COVID-19 lockdown over India is crucial as India is one of the regions with high seasonal variability of CH4. The present study has analyzed the tropospheric CH4 trends over India during the pre-monsoon season (March–May) for 2003–2021 using AIRS data. The study analyzed the lockdown variations (24 March–31 May) of tropospheric CH4 over India with the same period of 2019 and 2021 using TROPOMI to find the changes in CH4 concentrations over different regions of India due to lockdown. Our results capture the undeviating north (low)–south (high) gradient in the CH4 concentration with anticipated regional intensifications, likely, in the eastern and western coastal regions, with more comprehensive details than it ever has been presented before.

Crystalline ZnO Photocatalysts Prepared at Ambient Temperature: Influence of Morphology on p-Nitrophenol Degradation in Water

Since the Industrial Revolution, technological advances have generated enormous emissions of various pollutants affecting all ecosystems. The detection and degradation of pollutants has therefore become a critical issue. More than 59 different remediation technologies have already been developed, such as biological remediation, and physicochemical and electrochemical methods. Among these techniques, advanced oxidation processes (AOPs) have been popularized in the treatment of wastewater. The use of ZnO as a photocatalyst for water remediation has been developing fast in recent years. In this work, the goals are to produce ZnO photocatalysts with different morphologies, by using a green sol-gel process, and to study both the influence of the synthesis parameters on the resulting morphology, and the influence of these different morphologies on the photocatalytic activity, for the degradation of an organic pollutant in water. Multiple morphologies were produced (nanotubes, nanorods, nanospheres), with the same crystalline phase (wurtzite). The most important parameter controlling the shape and size was found to be pH. The photoactivity study on a model of pollutant degradation shows that the resulting activity is mainly governed by the specific surface area of the material. A comparison with a commercial TiO2 photocatalyst (Evonik P25) showed that the best ZnO produced with this green process can reach similar photoactivity without a calcination step.

Research on big data analysis model of multi energy power generation considering pollutant emission—Empirical analysis from Shanxi Province

With the development of the integrated energy Internet, energy structure optimization and emission reduction have led to higher requirements for developing various energy sources to enable coordinated and sustainable development. However, data-mining methods are rarely used to study the coordination of multi-energy generation in published research results. In this study, from the perspective of power industry emissions, coordinated generation of various energy sources, and balance of power generation and consumption, a data-mining algorithm was used to analyze the development of thermal power, hydropower, wind power, waste heat, gas, and other power sources. The chi-square automatic interaction detection tree (CHAID), logistic regression, and two-step clustering methods were applied. The results show that: a) CO2 and SO2 emissions were mainly affected by thermal power generation, whereas NOx emissions were jointly affected by thermal power, garbage power, and gas-fired power, and the emissions of various pollutants increased with an increase in power consumption. The optimal power-generation scheme under minimum emission can be obtained. b) There was a strong correlation between thermal power generation and residential electricity consumption, and renewable energy (wind energy, photovoltaic, hydropower) exhibited the highest correlation with the electricity consumption of the tertiary industry, which indicates that renewable energy generation can be promoted by managing electricity consumption in the tertiary industry. c) When the electricity demand of all users was small, the proportion of renewable energy power generation increased; in contrast, the thermal power generation was larger. This indicates the importance of improving the sustainable and stable power supply of renewable energy. This study provides a data analysis model for the coordinated development of multiple energies, which will contribute to the decision-making basis for controlling power emissions, improving the utilization rate of renewable energy, and optimizing the energy structure.

ESG/Green Investment and Allocation of Portfolio Assets

This article examines the current portfolio allocation in ESG and Green projects. Traditional investments focus on rates of return and risks associated with investment. Environmental, Social and Governance (ESG) or Green factors are additional components that investors have to pay attention to. Environmental protection is very important. However, as we see the current different definitions of ESG or Green factors lead to distorted allocations in portfolio investments. In order to bring portfolio allocations to a desirable direction, global taxation on pollution or creation of an accurate Green credit rating based on emissions of various pollutants are recommended.

Procena emisije zagađujućih materija od saobraćaja primenom mikrosimulacionih modela

Traditional traffic management methods are mainly focused on travel time optimization, ie minimizing control delay. The modern approach is increasingly emphasizing the minimization of negative impacts of traffic on the environment. Therefore, it is important to enable the evaluation of different traffic management strategies from the aspect of pollutant emissions. Microscopic simulation models enable detailed (second-by-second) representation of traffic flow, which creates a precondition for integration with emission models to enable this aspect of evaluating different management strategies. The paper presents the possibility of integrating the microscopic simulation model VISSIM and the emission model MOVES. It was concluded that this integration enables the comparison of different management strategies from the aspect of emissions of various pollutants.

Progress in organic fluorescent probes for detecting metal ions in environment

The massive emission of various pollutants leads to severe environmental problems, and the air and water issues attract enormous attention. Heavy metal ions highly affect our life and may cause many diseases, which is a critical issue to be solved. As reported, copper ion is highly related to some neurodegenerative diseases, such as Menkes and Wilson’s diseases. Children are susceptible to mercury ion during the early stages of development, leading to a variety of diseases relating to the brain, kidney and central nervous system. Thus, it is of vital importance to develop facile and fast detection methods for life-threatening metal ions. Organic dyes with various functional groups have shown great potential for detecting various metal ion pollutants through apparent color and fluorescence changes, exhibiting excellent selectivity and sensitivity. In terms of photophysical properties and chemical structures of organic dyes, we summarize recent research progress of the commonly seen detection mechanisms for metal ions. The detection mechanisms include photoinduced electron transfer (PET), intramolecular charge transfer (ICT), fluorescence resonance energy transfer (FRET), through-bond energy transfer (TBET), aggregation-disaggregation effect and rearrangement of molecular structures. As one of the mostly studied mechanisms, PET has been widely used in the construction of metal ion probes. These metal ion probes generally consist of three parts including fluorophores, spacers, and recognition sites. Most probes based on the PET mechanism are easily designed with high sensitivity and selectivity. However, most of these probes have no built-in correction, resulting in severe external environment interference. Compared with the PET mechanism, ICT mechanism has great superiority for the construction of ratiometric probes with built-in correction, which can minimize external interference and make quantitative detection more reliable. In addition, ICT mechanism provides another way for detecting some electron-donating and electron-accepting metal ions, such as Fe2+, Cu2+ and Zn2+. To achieve FRET within the probe, fluorophores are usually linked by a nonconjugated spacer, and the energy transfers from the donor to acceptor. In this scenario, spectral overlap is required. On the contrary, in TBET-based fluorescent chemosensors, a rigid conjugated linker is needed to chemically connect fluorophores and thus spectral overlap is not required. However, most of the reported FRET and TBET chemosenmsors are based on rhodamine dyes. It is highly necessary to develop novel energy transfer systems for expanding the variousness of metal ions probes. Naked-eye detection is the one of the most convenient methods for environmental metal ion sensing. Modulating the π-conjugated system of probes result in huge absorption spectrum change and lead to apparent color change of the probe, which is a promising strategy for developing naked-eye metal ions probes with high contrast. Moreover, mechanisms with aggregation-induced signal change including aggregation-caused quenching (ACQ) and aggregation-induced emission (AIE) are studied for environmental pollutant metal ion detection. Above all, these sensing strategies guarantee the successful development of metal ion probes. In this review, the basic design principles and responding mechanisms of the metal ion probes are discussed. Most of the probes can chelate with metal ions and some special reactions between probes and metal ions are also introduced including desulfurization reaction, redox reaction and Heck reaction etc. At last, the developing trends and the prospects of metal ion probes are presented.

Carcinogenic effects of indoor black carbon and particulate matters (PM2.5 and PM10) in rural households of India

Biomass is one of the prime domestic energy sources in the kitchens and about 60% of households are still using biomass and kerosene for cookingin India. These traditional cooking practices are incompetent as the use of biomass in traditional cookstove produces an enormous amount of carbonaceous aerosols that lead to indoor and outdoor air pollution. Emissions of various pollutants like black carbon (BC), PM10 and PM2.5 from burning of biomass cause serious health impacts like respiratory illness, lung cancer, watering of eyes, coughing, asthma and heart problems especially in women due to higher rate of inhalation of these fine particulate matters during the cooking period. Quantification of BC, PM2.5 and PM10 emissions from a different type of biomass in various types of kitchen arrangements and its associated impacts are poorly examined in India. Hence, daily concentrations of BC, PM2.5 and PM10 were monitored from different types of biomass user's households during January 2018 to December 2019 to assess indoor air quality by using aethalometer and nephelometer (pDR-1500) in three districts (Sitapur, Patna and Murshidabad) of Indo-Gangetic Plains (IGP) where approximately, 96% of rural families rely on biomass cooking. The highest mass concentrations were observed in biomass user's households and cow-dung cake users due to low calorific value. About 30.13% of PM10 and 35.89% of PM2.5 data exceeded the national ambient air quality standard on a daily basis in biomass user's households. A cancer risk assessment was also conducted in terms of mass concentration of these pollutants. The lifespan danger from exposure to BC was 4.33 × 10-7 in indoor for non-ventilated kitchens, 2.63 × 10-7 in indoor for ventilated kitchens, 3.98 × 10-7 in outdoor for separated kitchen, 3.22 × 10-7 for semi-open kitchen and 1.78 × 10-7 for open kitchen. The vulnerability assessment for cancer mortality under exposure of pollution was estimated to be highest for the age group of more than 50years whereas lowest for the age group of 0-4years for all kinds of kitchens in the study area.

Estimation Method of Pollutant Emissions in Certain Aircraft Flight

This paper intends to calculate the emissions of pollutants during the route flight quantitatively. In this paper, the flight dynamics model of the climb, cruise and descent phases are established respectively. Then, the pollutant emission estimation model of the aircraft is established based on the ICAO LTO model and the benchmark emissions data of engine manufacturers. Take certain civil aviation aircraft into account, a typical route is simulated, then the emissions of various pollutants at different flight stages are calculated and analyzed. Finally, several typical cruise strategies are selected for further comparative analysis. The results show that CO2 and NOX are the main pollutants during route flight. In addition, the pollutant emissions during the cruise phase are the highest, and the pollutant emissions during route flight can be effectively reduced by choosing the appropriate cruise strategy. The research results can be used to quantify and analyze the impact of flight performance optimization on civil aviation energy conservation and emission reduction, so as to better satisfy the requirements of green operations while ensuring flight safety.

Estimation and prediction of pollutant emissions from agricultural and construction diesel machinery in the Beijing-Tianjin-Hebei (BTH) region, China☆

Both agricultural and construction machinery are important non-road sources of atmospheric pollution, with total hydrocarbons (THC), nitrogen oxides (NOx) and particulate matter (PM) emissions accounting for more than 60% of the total emissions from all non-road mobile sources in China. However, there exist relatively few efforts to establish the emission inventory for these machineries. This study attempted to estimate and predict air pollutant emissions from agricultural and construction diesel machinery, using the Beijing-Tianjin-Hebei (BTH) region as the case study area. The results show that total emissions of PM10, PM2.5, THC, NOX, CO and SO2 in 2015 were 41.10, 38.80, 86.14, 520.41, 379.01 and 17.32 Kt respectively. The contribution of agricultural machinery was slightly higher than that of construction machinery, accounting for 60–71% of the total. Moreover, emissions of various pollutants (except SO2) from agricultural machinery were mainly distributed in central Hebei (Cangzhou, Shijiazhuang and Baoding), while emissions from construction machinery were mainly distributed in Beijing and Tianjin. The prediction suggest that the total emissions of agricultural and construction diesel machinery in the BTH region would increase by 6% in 2020 and 9% in 2025. Moreover, pollutant emissions from construction machinery would contribute from 29% to 40% in 2015 to 34%–61% in 2025. These results could provide important information for making effective mitigation measures of non-road mobile sources.

PM2.5-Associated Health Impacts of Beehive Coke Oven Ban in China.

Historically, beehive coke ovens (BCOs) were extensively operated in China and emitted large quantities of pollutants, including primary PM2.5 and secondary PM2.5 precursors, and other climate forcers. Although these ovens were legally banned in 1996 by the Coal Law, the process of phasing them out took over a decade to accomplish. Based on historical operation data derived from remote sensing images, temporal trends and the spatial distribution of the emissions of various pollutants from BCOs were compiled and used to model the resulting perturbation in ambient PM2.5, population exposure, and PM2.5-associated adverse health impacts. Historically, PM2.5 originating from BCOs affected a vast region across China, which peaked in approximately 1996 and decreased afterward until the ovens' final elimination in 2011. According to the results of a supply-demand model, emissions from the BCOs would have continued to increase after 1996 if they had not been banned. As a result, national average PM2.5 attributable to BCOs in 2014 would have been more than three times as high as that in 1996. It was estimated that the cumulative number of premature deaths associated with BCO-originating PM2.5 from 1982 to 2014 was as high as 365 000 (95% confidence interval 259 000-402 000). The number would have nearly tripled if BCOs had not been banned and halved if the ban had been implemented immediately after the regulation was in force, suggesting the importance of legislation implementation.