Concentration Of Gas Emissions Research Articles

Risk of climate change to sweet potato cultivation in the American continent

ABSTRACT Sweet potato, Ipomoea potatoes L., is an essential crop for food security in various countries. However, the effects of climate change could reduce or increase the yield and profitability of this crop, especially for small farmers. Thus, we developed species distribution models for the current and six climate change scenarios based on environmental variables, species occurrence, and global climate change model. Also, we identified the most relevant environmental variables for cultivation. Future scenarios showed gradual shifts in suitable areas for cultivation. Losses in suitable areas were more relevant than gains at the low concentration of greenhouse gas emissions (RCP 2.6). This trend is maintained in the worst scenario of a high concentration of greenhouse gas emissions (RCP 8.5) with more significant losses of suitable areas. The temperature and precipitation of warmest and wettest quarters, temperature seasonality, and isothermality are the most critical variables for sweet potato cultivation. The cultivation is expected to expand the suitable areas in some regions and retract in others due to climate change. Knowledge about climate change effects in cultivated areas is essential for developing management plans that could mitigate the adverse effects of climate change.

Modeling the potential distribution of the energy tree species Triadica sebifera in response to climate change in China

As an important woody oilseed species in China, Triadica sebifera is not only concerned with the substitution of traditional energy sources, but also plays a considerable role in coping with energy shortages. Accurately predicting the potential geographic distribution of Triadica sebifera in China and understanding its ecological needs are crucial for alleviating the energy crisis and effectively implementing energy substitution strategies. In this study, the potential geographic distribution of Triadica sebifera in China at contemporary and future periods was predicted based on the distribution data of Triadica sebifera in China and the environmental factor variables by Maxent model and ArcGIS software. The combination of important factors governing the potential geographic distribution of Triadica sebifera was assessed by the contribution of environmental factor variables. The accuracy of Maxent model's predictions was assessed by AUC values, TSS values and Kappa statistics. The results show that: High AUC and TSS values indicate high accuracy and performance of the model. The crucial environmental factors limiting the potential geographic distribution of Triadica sebifera are the temperature factor (mean air temperature of the driest quarter), precipitation factor (precipitation of the coldest quarter, precipitation of the wettest month), and the intensity of human activities (hf). The total suitable area for Triadica sebifera is 233.64 × 104 km2, primarily located in Yunnan, Sichuan, Hubei, Guizhou, Jiangxi, Guangdong province and Guangxi Zhuang Autonomous Region; its high suitability area is 30.89 × 104 km2, accounting for 13.22% of the total suitable area, mainly distributed in Jiangxi, Sichuan and Hunan provinces in the shape of a cake. Under the four typical greenhouse gas emission concentration patterns in the 2050s and 2070s, the areas of high and medium suitable areas for Triadica sebifera will increase, while the area of its low suitable area will decrease. However, the total suitable area will remain relatively unchanged. Its potential suitable habitats show a trend of shifting towards lower latitudes and southeast regions. The study predicted the pattern of Triadica sebifera under different climate change conditions, which can provide guidance for future cultivation of Triadica sebifera as well as for biofuel development and utilization.

The ecological suitability area of Cirsium lineare (Thunb.) Sch.-Bip. under future climate change in China based on MaxEnt modeling.

Many kinds of medicinal ingredients occur in Cirsium lineare that have good clinical efficacy, conferring on this species its high medicinal development value. However, with a rapidly changing global climate, it is increasingly imperative to study the factors affecting the habitat distribution and survival of species. We predicted the current and future distribution areas of suitable habitats for C. lineare, analyzed the importance of environmental variables in influencing habitat shifts, and described the alterations to suitable habitats of C. lineare in different periods (modern, 2050s, and 2070s) and scenarios (RCP2.6, RCP4.5, and RCP8.5). The results show that, under the current climate, the total suitable area of C. lineare is about 2,220,900 km2, of which the highly suitable portion amounts to ca. 292,600 km2. The minimum temperature of the coldest month, annual precipitation, and mean daily temperature range are the chief environmental variables affecting the distribution of habitat for C. lineare. In the same period, with rising greenhouse gas emission concentrations, the total suitable area will increase. In general, under future climate change, the suitable habitat for C. lineare will gradually migrate to the west and north, and its total suitable area will also expand. The results of this experiment can be used for the conservation and management of the wild resources of C. lineare. We can choose suitable growth areas to protect the medicinal resources of C. lineare through insitu conservation and artificial breeding.

Characterisation of Smoke Particles from Lithium-Ion Battery Fire: Morphology, Size and Composition

The electrification of the transport sector is a necessary step to reduce the concentration of greenhouse gas emissions (GHGs) in the atmosphere in order to mitigate climate change. Li-ion batteries (LIBs) are considered a key enabling technology and are crucially important for the green energy transition. However, LIBs may pose safety concerns, as demonstrated by the recurrent fire accidents involving electric vehicles, according to news reports from recent years. Several studies concentrated mainly on the identification, composition and flammability of vented gases during LIBs thermal runaway and fires. Scarce work about the particle emissions during a LIB fire can be found in the literature. To fill up this research gap, in this study, we characterised smoke particles from Li-ion battery fire using Scanning Electron Microscopy/Energy Dispersive X-ray spectroscopy (SEM/EDX) and X-ray Diffraction (XRD) to evaluate their size, morphology, crystallographic and chemical composition. Our results show that battery fire smoke particles contain chemical components and crystallographic phases that are toxic for health and environment. Moreover, we confirm the presence of (ultra) fine particles, reported previously, which due to their small size are inhalable and can therefore pose a serious risk to human health. Recommendations for further experimental studies are outlined to establish e.g. a correlation between smoke particles emissions and battery SOC, chemistry, abuse scenario, etc.

Climate and local environment co-mediate the taxonomic and functional diversity of bacteria and archaea in the Qinghai-Tibet Plateau rivers

Understanding the environmental response patterns of riverine microbiota is essential for predicting the potential impact of future environmental change on river ecosystems. Vulnerable plateau ecosystems are particularly sensitive to climate and local environmental changes, however, the environmental response patterns of the taxonomic and functional diversity of riverine microbiota remain unclear. Here, we conducted a systematic investigation of the taxonomic and functional diversity of bacteria and archaea from riparian soils, sediments, and water across the elevation of 1800– 4800 m in the Qinghai-Tibet Plateau rivers. We found that within the elevation range of 1800 to 3800 m, riparian soils and sediments exhibited similarities and stabilities in microbial taxonomic and functional diversity, and water microbiomes were more sensitive with great fluctuations in microbial diversity. Beyond the elevation of 3800 m, microbial diversity declined across all riverine matrixes. Local environmental conditions can influence the sensitivity of microbiomes to climate change. The combination of critical climate and local environmental factors, including total nitrogen, total organic carbon, as well as climate variables associated with temperature and precipitation, provided better explanations for microbial diversity than single-factor analyses. Under the extremely adverse scenario of high greenhouse gas emission concentrations (SSP585), we anticipate that by the end of this century, the bacterial, archaeal, and microbial functional diversity across the river network of the Yangtze and Yellow source basin would potentially change by −16.9– 5.2 %, −16.1– 5.7 %, and −9.3– 6.4 %, respectively. Overall, climate and local environments jointly shaped the microbial diversity in plateau river ecosystems, and water microbiomes would provide early signs of environmental changes. Our study provides effective theoretical foundations for the conservation of river biodiversity and functional stability under environmental changes.

Theoretical and experimental research on the use of hydrogen in the automotive spark ignition engine

Reducing the level of pollutant emissions of internal combustion engines requires the adaptation of solutions that improve the combustion process in the cylinder but those solutions may increase their constructive complexity. For this reason, the use of hydrogen is an effective solution, both for replacing fossil fuels and for reducing the concentration of pollutant emissions. The use of hydrogen as an additional fuel for the automotive spark ignition engines offers the possibility of obtaining increased energy performance, decreased pollutant emissions level and decreased concentration of greenhouse gas emissions. The paper presents the results of the some theoretical and experimental investigations carried on an automotive spark ignition engine, analysing the influence of the hydrogen on combustion and implicitly on energy performance and pollution. The simulation of thermo-gas-dynamic processes in the cylinder of the engine fed successively with gasoline/gasoline and hydrogen, allowed the authors to develop a specific and efficient procedure for conducting experimental investigations. The results of the theoretical and experimental research obtained and presented in the paper highlight the advantages of using hydrogen as an additive to gasoline fuelling in the automobile spark ignition engine: the improvement of combustion (reduction of combustion duration, increase of indicated thermal efficiency, reduction of specific energy consumption) and reduction of the level of polluting emissions and of the emission of greenhouse gases. An engine adjustment strategy for the sharp reduction of the concentration of nitrogen oxides is also presented.

Experimental study of deep and flexible load adjustment on pulverized coal combustion preheated by a circulating fluidized bed

Peak shaving of coal-fired power plants is a key to promoting renewable energy generation in a grid system. In this study, the deep and flexible load regulation characteristics of pulverized coal preheating combustion are explored. The determination criteria of the variable load related to the preheating temperature, preheated coal gas, combustion temperature and main flue gas (NO, N2O, CO and O2) emission concentrations are established, and the temperature hysteresis coefficient is introduced to characterize the hysteresis of the combustion process. The results show that this system has a deep load regulation capability and can operate stably over a wide load range from 25% to 113%. The chemical reactivity of the pulverized coal is enhanced with thermal modification, which ensures stable combustion in the combustion chamber at ultralow loads. Moreover, the optimal rate of variable load is achieved when the load step is 25%, and the maximum rates of variable load for the preheating process and combustion process are 4.17%/min and 3.13%/min, respectively. Furthermore, an excessively high load step will trigger a large amount of combustion hysteresis, which negatively affects the variable load process.

Methane Concentration Forecasting Based on Sentinel-5P Products and Recurrent Neural Networks

The increase in the concentration of geological gas emissions in the atmosphere and particularly the increase of methane is considered by the majority of the scientific community as the main cause of global climate change. The main reasons that place methane at the center of interest, lie in its high global warming potential (GWP) and its lifetime in the atmosphere. Anthropogenic processes, like engineering geology ones, highly affect the daily profile of gasses in the atmosphere. Should direct measures be taken to reduce emissions of methane, immediate global warming mitigation could be achieved. Due to its significance, methane has been monitored by many space missions over the years and as of 2017 by the Sentinel-5P mission. Considering the above, we conclude that monitoring and predicting future methane concentration based on past data is of vital importance for the course of climate change over the next decades. To that end, we introduce a method exploiting state-of-the-art recurrent neural networks (RNNs), which have been proven particularly effective in regression problems, such as time-series forecasting. Aligned with the green artificial intelligence (AI) initiative, the paper at hand investigates the ability of different RNN architectures to predict future methane concentration in the most active regions of Texas, Pennsylvania and West Virginia, by using Sentinel-5P methane data and focusing on computational and complexity efficiency. We conduct several empirical studies and utilize the obtained results to conclude the most effective architecture for the specific use case, establishing a competitive prediction performance that reaches up to a 0.7578 mean squared error on the evaluation set. Yet, taking into consideration the overall efficiency of the investigated models, we conclude that the exploitation of RNN architectures with less number of layers and a restricted number of units, i.e., one recurrent layer with 8 neurons, is able to better compensate for competitive prediction performance, meanwhile sustaining lower computational complexity and execution time. Finally, we compare RNN models against deep neural networks along with the well-established support vector regression, clearly highlighting the supremacy of the recurrent ones, as well as discuss future extensions of the introduced work.

Sustainable developments in near-dry electrical discharge machining process using sunflower oil-mist dielectric fluid.

In this study, a near-dry electrical discharge machining (NDEDM) process has been conducted using compressed air mixed with a low quantity of biodegradable refined sunflower oil (called oil-mist) to investigate the machining characteristics. The Box-Behnken method looks at how oil flow rate (OR), air pressure (AR), spark current (SC), and pulse width (PW) affect gas emission concentration (GEC), material removal rate (MRR), and surface roughness (SR). The TOPSIS (The Technique for Order of Preference by Similarity to the Ideal Solution) technique estimates the parameter optimal set for the best machining characteristics. The optimal machining parameters have been used to examine the microstructure of the machined surfaces using a scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDS) analysis. The 0.981mg/min of GEC, 55.145mg/min of MRR, and 2.43µm of surface roughness have been attained by the 14ml/min flow rate, 7bar of air pressure, 10 A spark current, and 48µs pulse duration of the sun-flower oil-mist NDEDM process.

Projection of Meteorological Dryness/Wetness Evolution Based on Multi-Model Scenarios in Poyang Lake Basin, China

Based on the projections of three shared socioeconomic pathways (SSPs) scenarios of three climate models of CMIP6, this study analyzed the standardized precipitation evapotranspiration index (SPEI) to understand the future meteorological dryness/wetness changes in the Poyang Lake basin (PLB) from 2021 to 2100. The effect of temperature change on the dryness and wetness variation was explored by comparing the trends of SPEI and standardized precipitation index (SPI) at multiple-time scales and different SSPs scenarios. The results indicate that the frequency of drought events may increase by 1.1~3.8% than the historical period in the three scenarios, and they may be higher than that of wetness events in the future of this century. Cumulative months of drought events are higher in most decades than the wetness events, and especially in the 2090s. A total of 43 months may suffer drought events in the 2090s under the SSP585 scenario, which is more than twice the wetness events. With the enhanced concentration of greenhouse gas (GHG) emissions, both the frequency of droughts and the proportion of extreme droughts show a significant increasing trend at 99% confidence in PLB. The spatial distribution of net precipitation is generally in the southwest–northeast pattern, yet it is still in different values in most scenarios; thus, the uncertainty of dryness/wetness spatial conditions should be considered. The SPI detects more wetness events and a more intensive wetting trend, while the SPEI shows the opposite. The difference between SPI and SPEI gradually increases with GHG emission concentration, and may even lead to contrary conclusion in the last two decades at a 48-month scale under the SSP245 and 585 scenarios, indicating the unneglectable impact of increasing temperature and evapotranspiration on the dryness/wetness conditions in the future. The research results can help to predict the evolution pattern of dry and wet occurrence in the PLB in the future and promote flood/drought control and disaster mitigation.

Farmers coping strategies to climate change in sustainable Arabica coffee production

Geographical Indications of Gayo Arabica coffee is currently faced with various challenges, including climate change, causing stagnation and, eventually, a decline in productivity. This research aims to determine the strategies adopted by farmers in dealing with climate change, to increase and maintain Gayo coffee productivity. The research was conducted in the Gayo Highlands, particularly in Aceh Tengah, Bener Meriah, and Gayo Lues districts, in three stages, including; (1) a study of the Gayo coffee GI area, (2) climate change study, and (3) a study of farmers’ strategies for dealing with climate change, using field observation surveys and interviews with farmers. The results reveal that the GI of Gayo arabica coffee has been mapped since its designation in 2010. Additionally, both rainfall and temperature have changed since the 1980s, and climate change (particularly temperature) has resulted in habitat shifting for the cultivation of arabica coffee clones, coffee berry borer infestations, and a decrease in coffee productivity. Farmers in the Gayo Arabica coffee GI area address climate change by implementing a strategy to create a microclimate through adaptation and mitigation. These include efforts to adapt coffee clones to their growing habitat, creating a microclimate by planting coffee and denser shade, covering the soil surface to minimize evaporation, and reducing the concentration of carbon dioxide gas and greenhouse gas emissions in the air by using locally sourced organic matter as fertilizer.

Climate refugia for Buchanania cochinchinensis (Lour.) M.R.Almeida, an important non-timber forest tree species, declining from its natural range in India

ABSTRACT Buchanania cochinchinensis, a socio-economically important forest tree species, faces high levels of exploitation. Originated from the Indian subcontinent, little is known about the patterns of the habitat distribution and the important climatic factors that shape its suitability. Using high-resolution environmental data for current and future climate scenarios, we studied the present and the future suitable habitats for B. cochinchinensis by MaxEnt. We evaluated the important bioclimatic variables that shape its distribution and identified distribution shifts under different climate change scenarios. Precipitation of wettest quarter, precipitation seasonality and altitude were identified as the most critical factors shaping B. cochinchinensis distribution. The future projections under RCP2.6 (with low concentration of greenhouse gas emissions) indicate increase in the distribution range of the species. Under the scenario with higher concentrations of emissions (RCP8.5), the suitable habitat range of B. cochinchinensis has decreased. Our results showed that the refugia for B. cochinchinensis under climate change occur in Central India, especially Madhya Pradesh and Chhattisgarh.

Analysing the Impact of Carbon Emissions and Non-Renewable Energy Use on Infant and Under-5 Mortality Rates in Europe: New Evidence Using Panel Quantile Regression

This study critically examines the health-environment discourse and uses infant and under-5 mortality rates, carbon emissions, and non-renewable energy to investigate the inherent associations. We argue that the concentration of greenhouse gas emissions is considered to increase and can undermine the access to basic resources necessary for leading a healthy life, such as access to food, water, health, and the environment. Environmental health is closely linked to human health. The world is witnessing a substantial increase in greenhouse gas emissions, which pose a significant threat to both environment and human health. Hence, this study contributes to the discourse with unbalanced panel data on 46 European countries from 2005 to 2015 to investigate the impact of carbon emissions and non-renewable energy on infant and under-5 mortality rates. Consistent findings from static and dynamic analyses reveal that (1) carbon emission is positively associated with mortality rate; (2) non-renewable energy shows a significant negative relationship; (3) persistency in mortality rates exists; (4) positive (negative) association of emissions (non-renewable energy) dwindles (increases) in absolute value at higher distributions of mortality rates; and (5) Euro Union countries show lower mortality rates relative to non-Euro Union members. Policy recommendations are discussed.

Mapping of Greenhouse Gas Concentration in Peninsular Malaysia Industrial Areas Using Unmanned Aerial Vehicle-Based Sniffer Sensor

The increasing concentration of greenhouse gas (GHG) emissions due to increased fossil fuel consumption for manufacturing activities to support population growth is worrisome. Carbon dioxide (CO2) and methane (CH4) remain the two GHGs that contribute to the impact of global warming, and inventorying their concentrations is important for monitoring their changes, which can be used to infer their emissions over time. Hence, this article highlights sniffer4D, an unmanned aerial vehicle (UAV)-based air pollutant mapping system that visualise and analyse three-dimensional (3D) air pollution data in real time, for mapping GHGs concentrations within industrial areas. Consequently, GHGs concentrations for two industrial and adjacent residential areas in Johor, Peninsular Malaysia were mapped. The GHGs concentrations were validated using a ground-based portable gas detector. The results revealed that CO2 has the highest concentration mean of 625.235 mg/m3, followed by CH4 with a mean of 249.239 mg/m3. The mapped UAV GHG concentration also reported good agreement with the in situ observations with an RMSE of 7 and 6 mg/m3 for CO2 and CH4 concentration, respectively. Ozone and nitrogen dioxide mixture (O3 + NO2) with a mean concentration of 249 μg/m3 and an RMSE of 9 μg/m3 are the remaining significant concentrations reported. This approach shall assist in fast-tracking the United Nations climate change mitigation agenda.

Factors Behind the Establishment and Fulfillment of Norway-Indonesia REDD+ Partnership (2010-2019)

The concentration of Greenhouse Gas (GHG) emissions creates non-boundary effects. Fighting the problem requires cooperation among states. As a developed country, Norway has continuously shown its support towards the addressing ecological issues both domestically and globally. The government actively engages in international environmental discussion and amplifies its status in the forum through financial contribution and consultation. As part of the Norway’s environmental diplomacy to be a global environmental leader, the country actively offers a partnership to developing countries with forest problems, including Indonesia, through Norway-Indonesia REDD+ partnership. By using the International Cooperation and Domestic Political Institution theories, this research aims to identify the factor behind the establishment and fulfilment of Norway-Indonesia REDD+ bilateral agreement. Ultimately, the study finds that the confidences that Norwegian government has towards Indonesia’s commitment on emission reduction pushes the offering of the partnership from the Norwegian government. Furthermore, the funds promised under the agreement attracts Indonesia to enter the agreement and fulfill it as it helps the country to achieve its forest-related emission reduction goals.

Optimization of green open space in Ambon City

The increase in population in Ambon City has resulted in increased space requirements and impacts the conversion of green areas into built-up areas. This indirectly impacts the decline in environmental quality, marked by an increase in the concentration of greenhouse gas (GHG) emissions in the air. The Green Open Space (GOS) arrangement program involves efforts to reduce GHG emissions in Ambon City. However, in reality, the allocation of space to develop green open space in Ambon City still does not meet the 30% standard or is still lacking 737.8 ha. This study aims to obtain information about the arrangement of green open spaces in Ambon City. The interview method was conducted in a structured manner with a questionnaire. SWOT analysis was used to analyze internal factors and external factors. The results showed that the critical strategies in optimizing Ambon City's green open space were to improve the quality of green open space by planting plants that have high GHG emissions absorption potentials, such as Samanea saman, Pterocarpus indicus, and Acacia mangium. Conduct harmonization and socialization with other institutions such as the Ambon City Satpol PP and green open space users to increase the supervision of green open space. Using the basic green coefficient as the primary condition for obtaining a Building Permit (IMB). The present study recommended that future research on green open spaces in Ambon City should focus on other influencing elements including geography, climate, socio-culture, and so on.

Using solar photovoltaic energy in urban water supply systems: a case study in Kayseri, Turkey

Abstract Submersible pumps, widely used in deep wells drilled to meet the water needs of users in urban areas, add an additional load to the conventional electricity grid infrastructure and are responsible for increasing the concentration of greenhouse gas emissions in the atmosphere. The main objective of this study is to investigate the technical and economic feasibility of using solar photovoltaic (PV) energy to reduce the net power drawn from the grid by submersible pumps in urban water supply systems. The Germiraltı catchment area (Kayseri, Turkey), which provides all of its energy needs from the city electricity grid, was chosen as the research area. Two different scenarios, ‘hybrid-powered water pumping system’ and ‘grid-connected PV system’, were analyzed and evaluated. A 1,620 kWp grid-connected PV system can inject 2,787.8 MWh/year of energy into the grid, which is more than the total annual energy need of the submersible pumps. The system operates with 85.7% performance ratio (PR), 19.6% capacity factor (CF) and 4.71 (h/d) final yield. The payback period of the system is calculated as 4.1 years. The results show that it is economically competitive to meet the energy needs of submersible pumps in urban water supply systems with solar PV energy.

Study on recovery and purification technology of sulfur hexafluoride gas under zero emission constraint

In order to improve the efficiency of sulfur hexafluoride gas recovery and purification, an optimization method of technical parameters for sulfur hexafluoride gas recovery and purification based on quantitative characteristic parameter analysis is proposed. Combined with the reaction temperature, concentration of sulfur hexafluoride gas, concentration of SF6 gas, NOx, CO and other sulfur hexafluoride gas, the technical index constrained programming model of sulfur hexafluoride gas recovery and purification was established by using the equivalent constraint and zero emission constraint analysis method. Combined with the experimental test analysis method, the entropy weight characteristic analysis model of sulfur hexafluoride gas recovery and purification was established, and the quantitative parameter analysis of sulfur hexafluoride gas recovery and purification was carried out by combining the comprehensive index parameter analysis. The entropy weight analysis technology is used to analyze the influence of different recovery and purification parameters on the concentration of sulfur hexafluoride gas, and a quantitative analysis model of sulfur hexafluoride gas emission concentration is established. According to quantitative characteristic parameter analysis and data fusion technology, the technical parameters of sulfur hexafluoride gas recovery and purification are optimized. The experimental results show that by optimizing the technical parameters of sulfur hexafluoride gas recovery and purification, the content of toxic substances in sulfur hexafluoride gas is reduced, the effective separation capacity of sulfur hexafluoride is improved, and the energy cost is reduced.

Study on the Mercury Migration in Clinker-Producing

Mercury is one most important global pollutants in the environment. The article studied the mercury migration according to the mercury migration in the cement process, in which a model for the relationship between the mercury input, internal circulation and output is built. In the model, mercury concentration in each stage of the process was calculated and characterized with different input, which were Consistent with actual verification, and then the reasonable method was advised to prevent the mercury pollution. The simulation showed that the mercury input is below 0.1g/t.cli, and the mercury gas emission concentration is below 0.05 mg/Nm3 whenever the mode of raw mill is on or off. But once the mercury input is over 0.23 g/t.cli, the mercury gas emission concentration is over 0.05mg/Nm3 although the mode of raw mill is on. The mercury content in ERM and KA is almost ten times higher than raw material, and the mercury content in KA is almost ten times higher than raw meal extraction, and multiples increase with higher mercury input as well. Even if mercury is continuously enriched internal, there is no limit of mercury concentration saturation.

An investigation on gas emission concentration and relative emission rate of the near-dry wire-cut electrical discharge machining process.

Wire-cut electrical discharge machining (WEDM) is the highly essential unconventional electrothermal machining process to cut the contour profile in the hard materials in modern production industries. The various environmental impacting contaminants (by evaporating and reacting liquid dielectric fluid) have been produced during the conventional WEDM process and are harmful to the machine operators. These wastes have been minimized by the near-dry WEDM process in which the pressurized air mixed with a small amount of water is used as a dielectric medium. In this research, influences of machining parameters (air pressure, flow rate mixing water, spark current, and pulse width) on gas emission concentration (GEC), material removal rate (MRR), and relative emission rate (RER) of near-dry WEDM process have been optimized by the Taguchi analysis. RER has been determined to analyze the variations of gas emission concentration per unit quantity of material removal by changing the process parameters. It was revealed that the maximum air pressure and flow rate of mixing water have been predicted as significant parameters on GEC and RER. While comparing wet and near-dry WEDM processes, the material removal rate of near-dry process is comparable to that of wet WEDM with minimum GEC and RER.