Petroleum substitution, greenhouse gas emissions reduction and environmental benefits from the development of natural gas vehicles in China

This study develops a bottom-up model to quantitatively assess the comprehensive effects of replacing traditional petroleum-powered vehicles with natural gas vehicles（NGVs） in China based on an investigation of the direct energy consumption and critical air pollutant（CAP） emission intensity, life-cycle energy use and greenhouse gas（GHG） emission intensity of NGV fleets. The results indicate that, on average, there are no net energy savings from replacing a traditional fuel vehicle with an NGV. Interestingly, an NGV results in significant reductions in direct CAP and life-cycle GHG emissions compared to those of a traditional fuel vehicle, ranging from 61% to 76% and 12% to 29%, respectively. Due to the increasing use of natural gas as a vehicle fuel in China（i.e. approximately 28.2 billion cubic metres of natural gas in2015）, the total petroleum substituted with natural gas was approximately 23.8 million tonnes（Mt）, which generated a GHG emission reduction of 16.9 Mt of CO2 equivalent and a CAP emission reduction of 1.8 Mt in 2015. Given the significant contribution of NGVs, growing the NGV population in 2020 will further increase the petroleum substitution benefits and CAP and GHG emission reduction benefits by approximately 42.5 Mt of petroleum-based fuel, 3.1 Mt of CAPs and 28.0 Mt of GHGs. By 2030, these benefits will reach 81.5 Mt of traditional petroleum fuel, 5.6 Mt of CAPs and 50.5 Mt of GHGs, respectively.

Medium-term Air Quality Benchmarking for Ecosystem Monitoring and Sustainability Planning: Case Study Dallas County (U.S.A.) 2015 to 2020

Medium-term air quality assessment,benchmarking it to recent past data can usefully complement short-term air quality index data for monitoring purposes.By using daily and monthly averaged data,medium-term air quality benchmarking provides a distinctive perspective with which to monitor air quality for sustainability planning and ecosystem perspectives.By normalizing the data for individual air pollutants to a standard scale they can be more easily integrated to generate a daily combined local area benchmark(CLAB).The objectives of the study are to demonstrate that medium-term air quality benchmarking can be tailored to reflect local conditions by selecting the most relevant pollutants to incorporate in the CLAB indicator.Such a benchmark can provide an overall air quality assessment for areas of interest.A case study is presented for Dallas County(U.S.A.)applying the proposed method by benchmarking 2020 data for air pollutants to their trends established for 2015 to 2019.Six air pollutants considered are:ozone,carbon monoxide,nitrogen dioxide,sulfur dioxide,benzene and particulate matter less than 2.5 micrometres.These pollutants are assessed individually and in terms of CLAB,and their 2020 variations for Dallas County compared to daily trends established for years 2015 to 2019.Reductions in benzene and carbon monoxide during much of 2020 are clearly discernible compared to preceding years.The CLAB indicator shows clear seasonal trends for air quality for 2015 to 2019 with high pollution in winter and spring compared to other seasons that is strongly influenced by climatic variations with some anthropogenic inputs.Conducting CLAB analysis on an ongoing basis,using a relevant near-past time interval for benchmarking that covers several years,can reveal useful monthly,seasonal and annual trends in overall air quality.This type of medium-term,benchmarked air quality data analysis is well suited for ecosystem monitoring.