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Currently, atmospheric emission inventory that includes multi-type pollutants and sources is still limited at the city level. This study developed a high-resolution emission inventory of eight pollutants based on detailed investigated data for Wuxi city in 2015. Results show that the total emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), total suspended particulates (TSP), particulate matter with an aerodynamic diameter of 10 μm or less (PM10), particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5), carbon monoxide (CO), ammonia (NH3), and volatile organic compounds (VOCs) were 36.9 kt, 95.2 kt, 287.3 kt, 127.8 kt, 46.0 kt, 626.4 kt, 10.9 kt, and 104.9 kt, respectively. Power plants were the major contributors of SO2 and NOx, accounting for 34.6% and 36.3% of the total emissions, respectively. Road dust was the dominant source of particulate matter, contributing 63.1%, 57.8% and 38.2% to the total TSP, PM10 and PM2.5 emissions, respectively. Around 67.0% of CO emissions were from iron and steel plants, while 50.1% of NH3 emissions were from livestock and poultry sectors. VOCs emissions largely came from oil refinery and chemical industry, with a share of 41.3%. High NH3 emissions were found in the southwest and northeast of Wuxi where high-intensity agriculture was located, while other pollutants were mainly concentrated on the eastern Wuxi where heavy industries, crowded traffic and highly dense population were located. Most pollutants from the industrial source exhibited the lowest value in February due to the Chinese Spring Festival with the exception of CO and NH3. This study helps to formulate the targeted air pollution control measures for Wuxi city by providing detailed information regarding the spatial-temporal distribution of multi-type air pollutants.

The composition and size of the passenger car fleet is often influenced by legislation and policy, including taxation, scrappage, and vehicle registration policies. Numerous measures at national and international level have been investigated to reduce the air pollution and/or climate change impacts of passenger fleets. However, the objectives of climate change and air pollution policy occasionally are conflicting, and this has resulted in a number of well publicised policy shortcomings. This paper outlines the development of a fleet emissions control (FEC) framework which enables the dynamic and adaptive optimisation of fleet emissions through changes in taxation policy in Ireland. The data for analysis was obtained from national sources including datasets from the national emission inventory and COPERT model. Applications of regression-based modelling and statistical analysis were conducted to predict fleet, mileage, and emissions changes. The results of the FEC framework showed that no increase in NOx emissions, above 2007 levels, could be achieved at a cost of a small increase in CO2 in 2016 (+1.8%). This could be achieved by taxation policy primarily resulting in a shift away from small engine diesel vehicles (

Haze is one of the most serious environmental problems in China, of which Beijing has been suffered from frequent haze events for years. As the major contributor of haze, PM2.5 emission needs more investigation, especially its driving forces that is crucial for mitigation and pollution control. In this study, the main contributors of PM2.5 emissions in Beijing were identified. By using the emission inventory and environmentally extended input–output framework, a structural decomposition model was employed to figure out the key drivers of the primary PM2.5 emissions in Beijing. The results showed that measures to control air pollution (e.g., the Beijing Clean Air Action Plan (2013–2017)) have caused PM2.5 emissions to decrease in recent years, indicating that emission mitigation strategies in Beijing are having preliminary success. Among all emission sources, due to large amounts of coke consumption, direct emission from residential energy consumption constitutes the largest proportion (31.05%–44.48%). Driven by fast urbanization and economic growth, high contribution of capital was invested to construction activities, which makes capital formation the largest driver of PM2.5 emissions from consumption perspective. PM2.5 emissions embodied in imports and exports also make a large proportion of consumption-based emission. Consumption volume and population growth are the main socioeconomic drivers to PM2.5 emissions increase, while emission intensity and consumption patterns offset the increase of emissions. The results will be useful developing PM2.5 emission mitigation measures and policies for Beijing and similar cities around the world.

Carbon emissions research in rapidly urbanizing areas around the world has typically focused on numerical changes in regional carbon emissions, and less research has been conducted on the spatial and temporal characteristics of carbon emissions from different sources in the urban system. Here, based on Multi-Resolution Emission Inventory for China (MEIC) modeling data, carbon emissions from industrial, power generation, residential, and transportation sources were analyzed in the Pearl River Delta region from 2008 to 2012, and the corresponding spatiotemporal distributions and main influencing mechanisms were elucidated. The results were as follows. (1) From 2008 to 2012, the total amount of carbon emissions increased gradually, and carbon emissions per unit area increased from 6513.65 × 103 gC∙m−2∙a−1 to 7519.03 × 103 gC∙m−2∙a−1, where industrial carbon emissions were the highest, followed by power and transportation emissions; residential carbon emissions were the lowest. (2) The spatial characteristics of carbon emissions in the Pearl River Delta region showed a carbon emissions belt with a shape similar to that of the number seven and Shenzhen carbon emissions center. Industrial carbon emissions resembled a “one belt, one center” pattern. Power carbon emissions mainly showed a “seven shape” pertaining to a carbon emissions belt and secondary carbon emissions centers. Residential carbon emissions were mainly located in the Guangzhou–Foshan carbon emissions belt and Shenzhen secondary center. Lastly, transportation-related carbon emissions were mainly located in the Guangzhou–Foshan and Shenzhen–Dongguan carbon emissions belt. (3) From 2008 to 2012, carbon emissions from industrial, transportation, and residential sources all showed obvious spatial distribution characteristics related to the carbon belt of Guangzhou–Foshan, and the two carbon emissions centers displayed a centripetal agglomeration development trend, in which the emissions gradually expanded out from around this area. The reasons were attributed to the influences of the “Guangfo One City” policy, whereby joint development in Guangzhou and Foshan is being focused on in its entirety. (4) The future development direction of the Pearl River Delta region should be based on controlling the scale of urban development, construction of low-carbon industrial production areas, and low-carbon-oriented land use planning; the formulation of such reasonable measures would help to reduce future carbon emissions.

Railways are treated as the lifeline of India, as they play a major role in the transportation of passengers and goods due to their cost effectiveness and large network. From 1970 to 2014, passenger and the net ton kms increased by a factor of 4 and 10, respectively. This significant increase in transportation demand was met by the transition of locomotives from steam to diesel and electric in the last few decades, as better energy efficiency led to lower operation costs. For policy making, emission inventory of locomotives is essential for better understanding of the relation between air quality and the choice of traction. However, the available national emission inventories developed by the top-down approach using the national fuel consumption statistics contain huge uncertainties due to non-consideration of activity data, such as age, power and type of locomotive. To estimate this uncertainty, for the first time, a bottom-up approach using link specific activity data was used to develop the emission inventory for North-eastern Indian states. In comparison to the bottom-up approach, the emissions calculated by top-down approach were lower in case of passenger transport (246% for NOx) and higher (36% for NOx) in case of goods transport. Further analysis indicated that, even though the estimated emissions were sensitive to emission factors used, role of activity data was more significant. Assuming that this difference is representative for other parts of the country, a national emission inventory for Indian Railways was developed using a modified top-down approach. Using the newly developed emission inventory for railways and the existing fuel based emissions for roadways, it was estimated that if road based freight transport is switched to rail, an average decrease of 58% and 50% of NOx and CO2, respectively can be achieved.

Unidad de excelencia María de Maeztu MdM-2015-0552 Altres ajuts: Programa CERCA - Generalitat de Catalunya Pesticides help to control weeds, pests, and diseases contributing, therefore, to food availability. However, pesticide fractions not reaching the intended target may have adverse effects on the environment and the field ecosystems. Modeling pesticide emissions and the link with characterizing associated impacts is currently one of the main challenges in Life Cycle Assessment (LCA) of agricultural systems. To address this challenge, this study takes advantage of the latest recommendations for pesticide emission inventory and impact assessment and frames a suitable interface for those LCA stages and the related mass distribution of pesticide avoiding a temporal overlapping. Here, freshwater ecotoxicity impacts of the production of feed crops (maize, grass, winter wheat, spring barley, rapeseed, and peas) in Denmark were evaluated during a 3-year period, testing the effects of inventory modeling and the recent updates of the characterization method (USEtox). Potential freshwater ecotoxicity impacts were calculated in two functional units reflecting crop impact profiles per ha and extent of cultivation, respectively. Ecotoxicity impacts decreased over the period, mainly because of the reduction of insecticides use (e.g., cypermethrin). Three different emission modeling scenarios were tested; they differ on the underlining assumptions and data requirements. The main aspects influencing impact results are the interface between inventory estimates and impact assessment, and the consideration of intermedia processes, such as crop growth development and pesticide application method. Impact scores for AS2 were higher than RS and AS1, but the differences in the crops ranking was less apparent. On the other hand, the influence on the estimation of impacts for individual AIs was considerable and statistical differences were found in the impact results modeled in scenarios RS and AS2. Thereby indicating the effect of inventory models on ecotoxicity impact assessment.

Inter-regional spillover of air pollution can be regarded as a mixture of economic externalities and long-distance transport. To comprehensively reveal this problem, a new consumption-based sulfur dioxide (SO2) emission inventory in 2010 for 30 provincial regions of China was compiled by introducing source-receptor relationship (SRR) model to integrate the spillover impacts of physical transport from the emitter (producer) region to the receptor region and virtual transfer from the driver (consumer) region to the emitter region. Compared the emissions induced by final regional demand with the emissions received in seven regions of China, Southern (0.59 Mt), Northern (0.25 Mt), Northwestern (0.18 Mt), and Eastern (0.14 Mt) areas outsourced SO2 pollution in the mass, whereas Central (−0.66 Mt), Northeastern (−0.42 Mt), and Southwestern (−0.08 Mt) areas took excessive environmental burdens in 2010. The four municipalities, Chongqing, Shanghai, Beijing, and Tianjin as well as the most affluent province Guangdong showed significant pollution transfer after an overall assessment of their roles in drivers, emitters and receptors. Shanxi, Inner Mongolia, Guizhou, Henan, and Shandong showed the largest co-benefits of SO2 emissions control for climate change mitigation. Japan was found to receive more portions of transboundary SO2 deposition than its market shares in China's export instead of other major trade partners of China. As a mega-city, Beijing induced significant SO2 emissions for power requirement, food consumption, miscellaneous services, and her vibrant research activities through the sectors of the power industry, coal mining, chemical manufacturing, food-related industries, petroleum processing and coking, but 86% of those emissions were outsourced by Beijing. In total, the spillover of SO2 emissions induced by Beijing was estimated at 0.20 Mt, 76 times more than its own share as a receptor across the supply chains. This study is competent for an analytic framework of strategic planning for joint prevention and control of air pollution in China and other countries. The results can help reduce pollution transfer, properly tax on drivers, effectively control the emitters, and reasonably compensate the receptors.

Urban air pollution has become a major concern in China. In the heavily populated and developed Beijing-Tianjin-Hebei (BTH) region, vehicle emissions are major pollution contributors. This paper aims to establish 2014 vehicle emission inventories for five major air pollutants in the BTH region: CO, HC, NOx, PM10 and PM2.5 and carry out an emission control policy scenario analysis based on the newly developed inventories. Results showed that total emissions of CO, HC, NOx, PM10 and PM2.5 from vehicles in the BTH region were 1622.4 kt, 187.5 kt, 544.7 kt, 23.5 kt, and 26.1 kt, respectively. Based on the emission inventory, high-resolution emission distribution maps of the study area were created at a scale of 1 km × 1 km by incorporating local traffic flow data. The CO, HC and NOx emission levels were higher in the southeast, while the PM10 and PM2.5 levels were relatively evenly distributed throughout the BTH region. Based on the emission inventories, four policy scenarios were set to simulate the emission changes, and results showed that eliminating old vehicles and upgrading oil quality could reduce emission efficiently. A policy of eliminating old vehicles was selected to calculate the economic cost. Results showed that the emission reduction efficiencies of unit cost decreased from Hebei, Tianjin to Beijing. The results of this study could help policy makers identify pollution sources and design appropriate control measures.

Agricultural machinery is an important non-road mobile source, which can exhaust multi-pollutants, making primary and secondary contributions to the air pollution. China is a significant agricultural country of the world; however, the agricultural machinery emissions research is at an early stage, and an emission inventory with a high temporal-spatial resolution is still needed. In this study, a comprehensive emission inventory with a high temporal-spatial resolution for agricultural machinery in China was first developed. The results showed that the total emissions in 2014 were 262.69 Gg, 249.25 Gg, 1211.39 Gg, 2192.05 Gg, 1448.16 Gg and 25.14 Gg for PM10, PM2.5, THC, NOx, CO and SO2, respectively. Tractors and farm transport vehicles were the top two greatest contributors, accounting for approximately 39.9%-53.6% and 17.4%-24.6%, respectively, of the total emissions of the five pollutants (except THC). The farm transport vehicles contributed the most (81.8%) to the THC emissions. The county-level emissions were further allocated into 1 km × 1 km grids according to source-specific allocation surrogates. The spatial characteristic analysis indicated that high emissions were distributed in northeast, north and central-south China. To obtain a high temporal resolution emission inventory, a comprehensive investigation on the agricultural practice timing in different provinces was conducted. Then, the annual emissions in the different provinces were distributed to a spatial resolution of ten-day periods (i.e. the early, mid- and late ten-day periods in each month). It was found that higher emissions in China occurred in late April, mid-June and early October. In addition, the emission uncertainty was also analyzed based on the Monte Carlo simulation. The estimated high temporal-spatial resolution emission inventory could provide important basic information for environmental/climate implications research, emission control policy making, and air quality modeling.

In order to achieve the targets underlined in the European Strategy for climate change and energy efficiency, the so called 20-20-20 package, the European Commission launched the Covenant of Mayors to endorse and support the efforts deployed by local authorities in the implementation of sustainable energy plans, and at the same time contribute to greenhouse gases emissions mitigation. This paper explores how the Covenant of Mayors (CoM) has been adopted in Portugal, and which type of measures are being defined and implemented by the municipalities. For that, all Sustainable Energy Action Plan (SEAP) submitted by Portuguese municipalities (124) have been examined, for which a detailed analysis was performed, including the Baseline Emission Inventory (70, i.e., around 50%). The municipalities that submitted SEAP cover 60% of the total population of the country because the main urban centres are a part of the 30% that have signed the CoM. Most common measures are related with changes on behaviour and infrastructure related to energy (such as renewable energies, energy efficiency in buildings, public lighting, etc.), waste and transport (for example optimization of: transport infrastructures, used vehicles and road operations). Public lighting is one of the energy measures present in all submitted SEAP, which plays a key role in energy consumption, reaching values of upwards of 12%, particularly in coastal areas due to higher population density and urban residential areas. Besides all efforts there is still a long way to go in terms of energy consumption reduction at local level.

Submitted by Núcleo de Pós-Graduação Administração (npgadm@ufba.br) on 2018-04-25T18:08:24Z No. of bitstreams: 1 Implementing city-level carbon accounting A comparison between Madrid and London.pdf: 612923 bytes, checksum: f2cebb5e2531d3bf8ad888a97c26a224 (MD5) Approved for entry into archive by Maria Angela Dortas (dortas@ufba.br) on 2018-05-02T20:50:40Z (GMT) No. of bitstreams: 1 Implementing city-level carbon accounting A comparison between Madrid and London.pdf: 612923 bytes, checksum: f2cebb5e2531d3bf8ad888a97c26a224 (MD5) Made available in DSpace on 2018-05-02T20:50:40Z (GMT). No. of bitstreams: 1 Implementing city-level carbon accounting A comparison between Madrid and London.pdf: 612923 bytes, checksum: f2cebb5e2531d3bf8ad888a97c26a224 (MD5) Previous issue date: 2018 A change of focus from the current production-based Greenhouse Gas (GHG) emissions inventory to an integrated production-consumption carbon accounting system would improve the quality of city-level inventories. London is one of the few cities in the world which has reported its GHG emission inventory using Consumption-Based (CB) methodologies. Although Madrid has adopted the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories (GPC) to report their GHG emissions, the city has never officially reported its GHG inventory using CB methodologies. Thus, the goal of this study is to analyze the challenges that must be faced by the production-based GHG emission inventory of Madrid in order to estimate GHG emissions from their supply chains and final consumers using the London's GHG emissions inventory experience. From the comparison between the 2010 GHG emission inventories of Madrid and London some challenges could emerge that Madrid's decision-makers might need to face regarding urban carbon accounting practices. As results, this paper shows that if GHG emissions from urban supply chains and final consumers are considered, the total GHG emissions reported by the Madrid inventory could double. This increase is similar to what London experienced when comparing production-based and integrated production-consumption GHG inventories. Besides, some difficulties related to lack of information were found when estimating GHG emissions associated with those goods and services consumed in Madrid. It would be useful to develop a full CB inventory using environmentally extended input-output (EEIO) matrices, more city-level primary data, and local cradle-to-grave factors, following the methodology applied by the London inventory. These actions would allow a more accurate calculation of urban supply chains and final consumer GHG emissions in Madrid. Finally, further research is recommended in order to improve the current knowledge about the contributions of the energy, transport and waste sectors to GHG emissions in both, Madrid and London.

Open biomass burning (OBB) significantly impacts regional and global air quality, climate change, and human health. Northeast China (NEC) is susceptible to OBB, including forest, shrubland, grassland, peatland, and cropland burning. Here, we develop a high-resolution (1 km × 1 km), multi-year (2001–2017), and monthly emission inventory associated with OBB in NEC using the burned area product (MCD64A1), satellite and observational biomass data, vegetation index-derived spatiotemporal variable combustion efficiency, and emission factors. The emissions produced from the burning of 11 types of crop-residues were calculated using measured and MODIS fire radiative power (FRP) data. The results showed that the average annual OBB emissions in NEC for 2001–2017 were 23.4, 95.1, 1538.0, 30,816.8, 18.8, 258.5, 69.8, 133.7, 225.3, 321.8, and 11.3 Gg of BC, CH4, CO, CO2, NH3, NMVOC, NOx, OC, PM2.5, PM10, and SO2, respectively. Taking CO2 as an example, crop residue burning was observed to be the largest contributor of CO2 overall, accounting for 68% (20.9 × 103 Gg a−1) of the total CO2 emissions, which was followed by forest (30%) and grassland (2%) fires. Heilongjiang Province was the largest emitter of CO2 (16.7 × 103 Gg a−1) compared to Jilin (5.8 × 103 Gg a−1), Inner Mongolia (5.3 × 103 Gg a−1), and Liaoning (3.0 × 103 Gg a−1). Crop residue burning was dominant in Heilongjiang, Jilin, and Liaoning, while forest fires were dominant in Inner Mongolia. Furthermore, CO2 emissions showed considerable interannual variability, with peaks in 2003 and 2008. Extensive burning of crop residues in the four provinces jointly determined these peak CO2 emissions, which occurred in March and October. Our high-resolution and multi-year inventory of OBB emissions can be applied to air quality modeling, atmospheric transport simulation, and biogeochemical cycling studies.

In 2008, the European Commission (EC) launched the Covenant of Mayors (CoM), a voluntary agreement under which local governments commit to reduce CO2 emissions by at least 20% within 2020, in order to reinforce local authorities in designing strategies to mitigate climate change in coherence with the European Union’s climate policy. The CoM may be defined as a coordinated collection of experiments based on common rules established by the EC. Cities signing the CoM commit to follow guidelines and standardized methodologies in setting CO2 emission reduction targets and in designing and implementing policies and measures to reach them, through the definition of key tools such as the Baseline Emission Inventory (BEI) and the Sustainable Energy Action Plan (SEAP). The present study analyses the emission reduction strategies of a sample of 124 cities with more than 100,000 inhabitants, signatories of the CoM, which delivered a SEAP by February 2014. More than 5500 actions planned by the sample cities were analysed and categorized. The most relevant actions in terms of recurrence and mitigation impact were assessed. Finally a set of variables was tested through a regression so as to determine their influence on emission reductions strategies. The main results of this study show that the sample cities accounted for a total of 370 million tons of CO2 emissions in selected baseline years and 94 million tons of intended emission reductions per year. The total emission reductions planned by cities reached 25% of the baseline emissions. Buildings and Transport stood out as the sectors where cities intend to deliver the largest emission reductions. Furthermore the analysis showed that cities’ administrations attribute higher potential to actions in subsectors under their direct control (municipal buildings, public transport, municipal fleet and public lighting) compared to actions in subsectors managed by private actors (households and firms). In the Building sector, the category of action delivering the highest share of CO2 emission reductions was represented by integrated actions, which combine several types of intervention so as to maximise the energy efficiency of buildings. In the transport sector, it was the modal shift, which implies a transition from private transport to public and cleaner transport modes. In both the Building and Transport sectors, cities plan to reduce the major amount of CO2 emissions through the implementation of management and organization, infrastructure construction and awareness-raising policy levers. Our results may be useful to urban policy makers to shape their mitigation strategies in coherence with cities’ commitments and plans and to replicate policies and actions on the basis of CoM signatories’ experiences.

Drinking water supply and wastewater treatment require significant energy inputs, and considerable greenhouse gas (GHG) emissions. Developing countries such as China are investing significantly in the construction of additional water infrastructure at the cost of increased GHG emissions. To understand the complexities of the inclusive impacts of GHG emissions from urban water systems, this study aims to examine both direct and indirect GHG emissions for water utilities in China's cities. A practical hybrid framework was proposed to reveal hidden GHG emissions via a combination of Intergovernmental Panel on Climate Change (IPCC) guidelines (bottom-up) and an Environmental Input-Output model (top-down). The study found that average annual GHG emissions between 2006 and 2012 from urban water utility operation in China accounted for 41 Mt CO2-eq, 58% came from energy use, 40% from treatment processes, and 2% from chemical use. Based on the proposed framework, Scope 3 emissions (indirect emissions other than electricity and heat purchase) for the operation of water utilities were estimated to be 8 Mt CO2-eq, which is significant to the total emission inventory; this corrected the bottom-up estimation in which 90% of Scope 3 emissions were not captured. The main hidden emission sources were upstream emissions of electricity and heat generation (21%), management of water conservancy (9%), manufacture of metal products (15%) and plastics (6%), and other chemical inputs (4%).Embodied emissions from cement and lime production (27%) and steel rolling of (22%) were the main sources of Scope 3 emissions for the construction of water infrastructure. Future variations of GHG emissions from water utilities were determined to be largely a result of the growth of wastewater treatment. This study demonstrates the feasibility of a hybrid approach to supporting low-carbon planning of water utilities from the viewpoint of water-energy-GHG nexus, and suggests that reduction of non-CO2 emissions in wastewater treatment and emissions of electricity consumption across supply chains has a significant potential to mitigate total GHG emissions from China's water sector.

The increased input of anthropogenic phosphorus to watershed ecosystems has caused eutrophication in the Yangtze River. Identifying total phosphorus (TP) sources is important for the management of watersheds. As a primary tributary of the Yangtze River, the Tuojiang River Basin (TJRB) plays important roles in the economy and ecology of the region. A watershed-level anthropogenic TP emission inventory was established using emission factors and loss coefficients for 2017 in the TJRB. The annual TP emissions to the TJRB were estimated to be 9253.55 t, of which livestock contributed 52.52%. The agricultural TP emissions to water bodies was 5201.87 t, followed by domestic emissions (3621.19 t) and industrial emissions (430.49 t). The TP contributions of the nonpoint sources were 3.07 times greater than those of the point sources. According to the Monte Carlo method, the uncertainty of TP emissions was [-69.71%, +68.06%] for the 95% confidence interval. Industrial emissions were identified as the largest contributor to the uncertainty [-33.75%, +38.37%]. The establishment of effective livestock breeding management practices along with the comprehensive utilization of facilities could help reduce TP emissions into the TJRB. This study presents an approach to the calculation of an estimated annual emission inventory of TP for the TJRB. The results enhance the fundamental data regarding pollution sources for subsequent research investigations.

Pakistan stands as the seventh most vulnerable country in the debate of climate change. The trail of changes occurring in the natural climate in the country is mainly linked to an increased level of CO2 emissions. These emissions come from massive coal combustion in the newly developed coal fired power plants in the country. In the absence of emission inventory after 2015, this study has deployed direct observation technique to measure CO2 emissions from all the seven coal fired power plants executed under China-Pakistan Economic Corridor. It has been found that the attempt to meet the energy needs of the country’s growing population has been resulting in 14,500 Mt CO2 emissions per annum. The energy production from impure energy sources is ending-up in 65% higher CO2 emissions than the normal trend. These massive emission scenario projects rose the global mean temperature up to 2.23° by 2020. The consistent rise in emission up to 226, 562, 500 Metric tons further corresponds to 7.6 °C rise in GMT in 2050. The study calls for the immediate use of pledged, but not applied, critical technology to halt CO2 discharge. Also, the country requires a shift to clean, green and renewable energy sources to ratify the Paris agreement.

Emission factors from the COPERT IV model were used to determine emission inventories of CO, NMVOCs, NO x , BC, OC, PM 2.5 and PM 10 for Shanghai, Jiangsu, Zhejiang and Anhui between 1999 and 2013. A GIS was used to analyze the spatial distributions of vehicular pollution in the Pan-Yangtze River Delta. Vehicular pollutants (CO, NMVOCs, NO x , BC, OC, PM 2.5 , and PM 10 ) emissions in all four provinces increased between 1999 and 2012. Emissions increased more slowly after 2011, and total emissions were lower in 2013 than in 2012. Emissions increased less in Shanghai than in the other provinces, and emissions in Shanghai decreased, following the enforcement of new vehicular emission standards. Emissions of NO x increased more than those of other pollutants, rising from 39,000 t in 1999 to 148,000 t in 2013. Passenger cars and motorcycles were found to be the main sources of CO and NMVOCs, and heavy duty trucks and buses were found to be the main sources of NO x , BC, PM 2.5 , and PM 10 . Emissions were found to be higher in coastal areas than in inland areas, and were found to be particularly high along the Yangtze River, Hangzhou Bay, and the area around Tai Lake.

China being a large developing country, with rapid economic growth over the last three decades, has a great challenge to control volatile organic compound (VOC) emissions and mitigate their related environmental issues and health problems. Moreover, China has great disparity in characteristics of VOC emissions and economic development among its 31 provincial regions. Local governments should suit their control measures to local conditions. To address this issue, we selected Jiangsu Province, one of the largest contributors of VOC emissions in China, having the second largest economy among the 31 Chinese provinces, as our example. Then we built a VOC emission inventory for the period 2000–2013 and set up a scenario analysis for the reduction of VOC emissions for Jiangsu Province. Results show that total VOC emissions in Jiangsu have risen from 0.98 Tg in 2000 to 2.15 Tg in 2013, and emissions related to solvent utilization and industrial processes account for 49.0% and 42.9% of the 1.17 Tg increase. Overall, VOC emissions were concentrated in Jiangsu's southern and coastal areas for the study period. Although per-gross-domestic-product VOC emission intensity is decoupled from urbanization ratio, Jiangsu's VOC emissions are strongly correlated with gross domestic product and urbanization ratio. In scenario analysis, only enhanced control measures involving cleaner production processes and more stringent end-of-pipe approaches can achieve the two controlled sources', i.e., industrial process' and solvent utilization's, total reduction rate of 24.6% by 2020, compared with 2013, which means such measures will realize the emission reduction goal, 24.3%, assumed for China's thirteenth five-year-plan period of national development.

Understanding the different impacts of urbanization on sectorial carbon dioxide (CO2) emissions at different spatial scales is of great importance for the evaluation of energy transition policies and reduction of environmental inequality. However, how urbanization affects the CO2 emissions of central heating systems at high spatial resolution in China has not been fully studied before. Based on satellite-observed NPP-VIIRS nighttime light (NTL) data, we develop a 5 km × 5 km annual CO2 emission inventory for coal boilers, thermal power plants (TPPs), and natural gas boilers in China’s central heating systems for the period 2012–2017 by using the geographical and temporally weighted regression (GTWR) model. It is observed that nonurban areas generated 2–4 times the CO2 emissions of coal boilers in urban areas. The largest increments of CO2 emissions of gas boilers are observed in urban areas of the eastern (6.80 times) and central regions (2.86 times) in 2013–2014, due to the clean heating policy in the “2 + 26” cities in China. The effects of urbanization on CO2 emissions from natural gas boilers are approximately 2–3 times those of coal boilers, and the differences are largest in western cities with only minor differences in northeastern cities. Our results will aid in designing low-carbon development goals and provide micro-level information on central heating facilities in urbanized and less developed regions.

In order to explore the establishment method of high-resolution vehicle emission inventory and analyze the temporal and spatial variation law of vehicle greenhouse gases (GHG) emissions. This paper proposes a bottom-up method based on road network information and the real-time average interval speed of road segments. A traffic speed-flow model is proposed to predict the hourly traffic flow and the localized Motor Vehicle Emission Simulator (MOVES) is used to simulate the CO2, N2O and CH4 emission factors. A high temporal (1 h × 1 h) and spatial (1 km × 1 km) resolution GHG emission inventory of motor vehicles in Beijing in 2018 is developed by this means. The actual emissions of CO2, N2O and CH4 are 19,864,590, 82 and 511 t, respectively. And the total GHG emission is 19,901,933 tCO2e combined with global warming potential (GWP). The daily GHG emissions on weekday and weekend are 55206.30 and 52817.64 tCO2e, respectively. There are three obvious peak emission periods on the weekday, namely, the morning peak (8:00–9:00), the noon peak (11:00–12:00) and the evening peak (18:00–19:00), which contribute 11.76%, 11.84% and 12.92% of the daily emission, respectively. The 1 h × 1 h emission grid shows the spatial distribution characteristics of emissions. The areas within the Fifth Ring Road (973 km2) are only 5.93% of the total area of the city (16,410 km2) but contribute 41.53% of the total vehicle GHG emissions. This study provides detailed data support for implementing vehicle GHG emission mitigation measures.

Iron and steel sector is the largest industrial energy consumer and emission source of greenhouse gas and air pollutants in China. Therefore, it is imperative to conduct a quantitative assessment for energy conservation potential and environmental benefits of China’s iron and steel industry. Energy efficiency improvement, EAF promotion and charcoal substitution are efficient measures to achieve cleaner and sustainable development. In this paper, five scenarios are designed for comprehensively analyzing the multiple factors influencing the potential for energy conservation and emission reduction. Furthermore, emissions reduction benefits of air pollutants are combined with Conservation Supply Curves to accurately evaluate the cost of the technology. A comprehensive emission inventory of air pollutants is established. The results show that under the synergistic effects of charcoal substitution, EAF improvement and energy efficiency improvement, significant environmental benefits have been achieved. Energy intensity was reduced obviously from 16.59 GJ/t-steel in 2017 to 14.46 GJ/t-steel in 2030 in integrated scenario, while the emission intensity of GHG, SO2, NOx, PM2.5, PM10, CO and VOCs in 2030 is decreased by 21.53%, 14.59%, 17.07%, 0.16%, 0.22%, 16.5% and 20.67% compared with business-as-usual scenario. In addition, combining Conservation Supply Curves with emissions reduction benefits can significantly reduce the cost of the technology, which has a great significance to the popularization and application of technologies. Sensitivity analysis in terms of discount rate and energy price is conducted. This study could help policy makers to cast light on the status quo and prompt more effective policies for China’s iron and steel industry.

A high–resolution emission inventory of primary air pollutants of 18 cities in Henan region, as the representative of central plains of China, was developed based on the combination of bottom–up and top-down methods. It was found that the emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), carbon monoxide (CO), particulate matter with an aerodynamic diameter of 10 mm or less (PM10), particulate matter with an aerodynamic diameter of 2.5 mm or less (PM2.5), Volatile Organic Compounds (VOCs) and ammonia (NH3) in 2016 were 780.4, 1682.9, 7152.8, 1440.3, 757.2, 1110.7, and 982.0 Gg, respectively. The emissions of the three major PM2.5 species, namely, Organic carbon (OC), Elemental carbon (EC), and sulfate ( S O 4 2 − ), were 161.2, 83.1, and 64.6 Gg, respectively. Stationary combustion was the largest contributor to SO2, NOx, CO, and PM2.5 emissions with 71.6%, 49.0%, 34.1%, and 24.7% contributions, respectively. Dust was the dominant source of PM10 emissions (42.4%), whereas industrial process was the largest contributor to VOCs emission (34.8%). Agricultural source contributed 87.7% of NH3 emission. The emissions were mainly distributed over the northwest and central part of Henan, and cities of Anyang, Zhengzhou, Luoyang, Pingdingshan, and Jiaozuo were the major contributors. Large NH3 emissions occurred during May to September, and high emissions of other pollutants were found from October to January. According to the Gini coefficients of per capital Gross Domestic Product (GDP) distribution among multiple air pollutants, the SO2 and NH3 emissions had high regional disparity, and the cities of Anyang and Zhengzhou had a high economic–environment inequity. Furthermore, this results were evaluated by comparing with other studies and the trend of spatiotemporal observed ambient concentration, which proves that the results are reliable. This work may benefit the government to further understand current local emission characteristics and formulation of targeted air pollution control measures.

Intelligent transportation systems (ITS) have emerged as essential measures to manage traffic congestion and to reduce vehicular emission and energy consumption, while their effectiveness has not been directly quantified under real-world driving conditions. By conducting real-world driving and emission measurements with a portable emission measurement system, we found that the usage of the speed guided-ITS (SG-ITS) significantly reduces fuel consumption and pollutant emissions (i.e., carbon monoxide, nitrogen monoxide, nitrogen dioxide, and particle number) of both tested vehicles (a light-duty gasoline car and a heavy-duty diesel truck) through decreasing the frequency of starts and stops, the strength of acceleration, and the time proportions of acceleration and idle. These reductions obtained from real-world measurements are higher than those predicted by vehicle emission models such as Motor Vehicle Emission Simulator (MOVES) and Computer Programme to calculate Emissions from Road Transport (COPERT). Reductions in fuel consumption and pollutant emissions due to the usage of the SG-ITS are most efficient on urban roads (low traffic) among all the three road types, while the most time saving can be obtained on urban roads (high traffic). By combining a high-resolution vehicle emission inventory, we estimate that the implementation of the SG-ITS may significantly reduce the total vehicular exhaust emissions of nitrogen oxides, carbon monoxide, total hydrocarbons, and particulate matter in Beijing by 15.9%, 20.5%, 23.9%, and 22.5%, respectively. Our study directly evaluates the benefits of using SG-ITS based on real-world measurements, highlighting that implementation of the SG-ITS can be a practical policy option in terms of efficiently reducing energy consumption, mitigating urban air pollution, and alleviating urban traffic congestion.

The petroleum refining industry is an important contributor to industrial volatile organic compounds (VOCs) emission. As a foundational work for VOCs control, previous VOCs inventories usually treated the petroleum refining industry as an integrated part resulting the unknown of VOCs emission characteristic among different units. Refined management has becoming an inevitability with the increasing strictness of environment standards. This study aims to develop a holistic method for VOCs emission inventory of the petroleum refining industry toward specificity, accuracy and economization, in which a source categorization was proposed from unit angle, and a systematic estimation method was developed from the material flow point of view. This method provides a more specific and accurate quantification method, especially for fugitive emission sources which is a pivotal but difficult problem in VOCs inventory establishment. Through application to a typical medium-scale refinery located in northern China, a unit-specific VOCs emission inventory with 48 emission sources and respective local VOCs emission factors (EFs) was established. Estimation results and economic cost of the developed method were compared with those of other methods. In this study, the integrated EF was 0.77 kg-VOCs/t-crude oil refined, which was in the same order with most previous studies. Inventory results implied that increasing hydrotreating unit, reducing chemical device and solvent-used unit (e.g., polypropylene production, furfural refining unit), upgrading catalytic reforming unit were beneficial to control VOCs emissions in this study. Using floating-roof tanks rather than fixed-roof tanks is an effective way to reduce VOCs emissions from storage tanks, which decrease 72%–86% of diesel storage emissions. Economic cost analysis showed that the advantage of this method lied in lower labor cost, and no subsequent monitoring cost. Suggestions proposed from this study provide feasible measures for local policy makers to control VOCs emission and determine abatement strategies of the petroleum chemical industry. Meanwhile, this study greatly helps enterprises promote the fine management of VOCs-containing materials from the overall processes to identify VOCs control emphasis.

To characterize the anthropogenic emissions of air pollutants (PM2.5, PM10, VOCs, NOx, SO2, and CO) in Shandong Province, eastern China, the high-resolution emission inventories were developed using the “bottom-up” methodology. The emission sources were categorized to biomass burning, dust, fossil fuel combustion, industrial processes, solvent utilization, waste disposal, and on-road vehicles, with five-level classification and 399 subclasses. Emission factors were collected from China’s guidelines on the emissions of atmospheric pollutants and literatures with local measurements. Particularly, those for on-road vehicles were calculated by COPERT v5. The county-level activity data were obtained from the governmental statistics. Results showed that the estimated anthropogenic emissions of PM2.5, PM10, VOCs, NOx, SO2, and CO in Shandong Province in 2016 were 5136.8, 5685.4, 3257.1, 1430.6, 240.6, and 19618.8 kt, respectively. The main emission source of PM2.5 and PM10 were dust and it was industrial processes for VOCs and CO. On-road vehicles and fossil fuel combustion contributed the most to NOx and SO2 emissions, respectively. The composition of emissions by sources for each pollutant differed among cities. Emissions in Shandong displayed remarkable spatial variations, with the highest in the central, southern, and coastal areas. This study could be expected to supply sufficient information and basic data for formulating effective environmental management policies and further improving the air quality in Shandong Province and even in Beijing-Tianjin-Hebei region.

This paper presents projections of global methane emissions from coal mining under different coal extraction scenarios and with increasing mining depth through 2100. The paper proposes an updated methodology for calculating fugitive emissions from coal mining, which accounts for coal extraction method, coal rank, and mining depth and uses evidence-based emissions factors. A detailed assessment shows that coal mining-related methane emissions in 2010 were higher than previous studies show. This study also uses a novel methodology for calculating methane emissions from abandoned coal mines and represents the first estimate of future global methane emissions from those mines. The results show that emissions from the growing population of abandoned mines increase faster than those from active ones. Using coal production data from six integrated assessment models, this study shows that by 2100 methane emissions from active underground mines increase by a factor of 4, while emissions from abandoned mines increase by a factor of 8. Abandoned mine methane emissions continue through the century even with aggressive mitigation actions.

The Environmental Kuznets Curve (EKC) hypothesizes an inverted U-shaped relationship between indicators of environmental quality and economic growth. The possible existence of an EKC has in the past been tested using relatively short time series of data and presumed indicators of environmental quality that can be considered sub-optimal. This paper addresses these shortcomings in investigating the extent to which economic growth and environmental quality in Singapore, the most economically developed country in Southeast Asia (SEA), accord with an EKC. A heavy metal (chromium, Cr) is here used as an indicator of environmental quality. This is because levels of a heavy metal with well-known risks to health are likely to have a much stronger relationship with perceptions of local environmental quality than, for example, CO2 emissions, and therefore likely to elicit a more rapid response from legislators. A national emission inventory (NEI) analysis quantified atmospheric Cr emissions from 1900 to 2017. Levels of Cr emissions increased rapidly during the 1960s–1980s, a period characterized by industrialization in Singapore that commenced around the time of its independence, returning to negligible levels by the 1990s as the country entered the current period of de-industrialization and economic modernization. Results of the NEI for the period post-1950, when an unbroken time series of reliable and annually comparable economic data first become available, were further subjected to econometric analysis, which confirmed the EKC hypothesis with regard to Cr emissions in Singapore. Results also suggest that the post-industrial development of Singapore may have contributed to creating pollution havens in the region. Together the findings have important implications for regional sustainable development and the governance of pollution emissions, including those that potentially have transboundary effects, more generally.

Emissions from heavy-duty diesel trucks (HDDTs) pose a major threat to environment and human health. Understanding the behavior of pollutant emissions from HDDTs facilitate the formulation of traffic-related policy measures to mitigate the adverse effects. This study proposes a new method to estimate the emission inventory of HDDTs and analyze their spatiotemporal evolution characteristics. Multi-source data were fused to provide a complete picture of the transport environment. With the idea of modeling pollutant emissions by “single vehicle” and “road segment,” emission inventories were constructed with different spatiotemporal scales using localized emission factors. A spatiotemporal cube model was introduced to represent the high-resolution emission inventory. A hot-spot and local-outlier analysis were conducted to explore the spatiotemporal evolution mechanism of pollutant emissions. The megacity of Tianjin in China was taken as the area for the case study. The average daily emissions of CO, NOx, PM, and VOC are 12,978.18, 48,675.22, 712.6, and 1217.72 kg d−1, respectively. Temporally, the pollutant emission had a significant peak at 06:00, 11:00, and 18:00 and was affected by major festivals. Spatially, the distribution pattern of emission was policy-driven and closely related to its spatial location. It increases radially outward from the outer-ring road to the periphery. The hot-spot analysis identified 16 pollutant emission patterns. The road segment with persistent cold spots accounted for 48.27% of the roads, mainly distributed within the outer ring road. The road segments with intensifying and persistent hot spots accounted for 19.04% of roads, mainly distributed on the intercity highway. The locations with outlier values reached 12,027, accounting for 31.90%. The key time intervals of the occurrence of the outlier pattern are 11:00–12:00 and 01:00–02:00. Road segments showing only the low–low cluster pattern is mainly located within the outer ring roads. Those with only low–high outlier pattern exhibits a relatively scattered spatial distribution, which is affected by the heterogeneous distribution of HDDTs.

High resolution modeling provides a more detailed representation of spatial gradient, which is critical for air quality and human exposure estimation studies. However, to date, no experimental investigations have directly addressed the question of whether high-resolution modeling can increase performance with respect to reproducing meteorological conditions in general; and to spatial distribution of air pollution specifically. In this study, we established a high-resolution Weather Research and Forecasting Model-Community Multiscale Air Quality Model with 1 km × 1 km horizontal resolution in the Beijing area. Compared with the 3 km resolution (Case 1), the more detailed land use and land cover in the 1 km resolution (Case 2) result in the improvement of 2-m temperature (T2), while the improvement of 10-m wind speed (WS10) mainly stemmed from implementation of the single urban canopy effect. The more accurate T2 and WS10 jointly lead to a decrease of Planetary Boundary Layer Height in the city. With a better spatially-resolved meteorological field and updated emission inventory, the urban PM2.5 monthly average in Case 2 surpasses Case 1 and the increment of PM2.5 increased alongside the pollution levels, especially above the heavy pollution level. Moreover, the differences in O3 and NOx monthly average between Case 2 and Case 1 negatively correlate across the space. In July, the temporal trend of O3 in Case 2 is closer to observation due to the improvement of T2. Correspondingly, compared to the Case 1, the population weighted PM2.5 concentrations are 2.33% higher while population weighted O3 concentrations are 1.99% lower in Case 2. Overall, the results of Case 2 better capture and reproduce the temporal trends and magnitudes of meteorological conditions and air quality.

Accounting for 7% of energy consumption from all industrial sectors and 15% of total greenhouse gas (GHG) emissions in China in 2009, the cement industry should be one of the main sectors to implement low carbon development. However, a detailed study on presenting its GHG emission trajectory and identifying the key driving factors has yet to be done. Under such a circumstance, this paper first presents a GHG emission inventory of the cement industry in China and then identifies the main driving factors that influence changes of GHG emissions in the cement industry by adopting LMDI method. Our results show that the total GHG emission in 2009 was 1095.1 Mt carbon dioxide equivalent (CO 2 e), of which 592.8 Mt CO 2 e was process-related and 502.3 Mt CO 2 e was energy-related. The major factors responsible for the increase of GHG emissions during 2005–2009 include cement production activity effect and clinker production activity effect, while energy intensity effect played a positive role to offset total GHG emissions. Finally, we present our policy implications and provide possible technical solutions for reducing GHG emissions of the cement industry in China.

Mexico has set a desirable 50% reduction goal of Greenhouse Gas emissions by 2050, compared to the 2000 baseline. In this regard, all the activity sectors, including universities and research institutions, are encouraged to adopt similar targets. As a contribution to the national efforts on the subject, this paper presents the 2010 Greenhouse Gas emission inventory of the Institute of Engineering at Universidad Nacional Autonoma de Mexico based on the academic and research activities developed in 2010. The inventory report, generated according to the Greenhouse Gas Protocol and under a consumption based methodology integrating life-cycle assessment, considers the following activity categories: electric energy generation, vehicle fleet, purchased electricity, commuting, air travels, courier shipments, paper consumption and solid waste. The total Carbon Footprint of the Institute of Engineering in 2010 was calculated in about 1577 tCO2e, where 42% of the Greenhouse Gas emissions were generated by the use of electricity, 50% by transportation; including its own fleet and commuting vehicles, 5% by air travel, 1% by shipments, 1% by use of paper and 1% associated to the final disposal of solid waste. Four scenarios of potential reduction are proposed based on changes in commuting activity. From the proposed scenarios, the one with a combination of teleworking and carpooling is the most effective.

The need to calculate greenhouse gas emissions (GHG emissions) has become more or less ubiquitous throughout the economy, both in public and private areas. As present, a diverse number of calculation methods are available for preparing GHG emission inventories. However, several questions remain unresolved since there is currently no uniformity regarding how to define ‘the waste management industry’. The present paper focuses on these problems. The objectives are: first, to provide an approach for setting up a GHG emission inventory for the waste management sector; and second, to consider the sensitive issue of setting system boundaries when establishing a GHG emission inventory and also to emphasise the considerable need for caution when doing so. The approach elaborated here is based on a comprehensive literature analysis and on a comparison of existing GHG emission calculation approaches, particularly with regard to the waste management sector. Since the issue of selecting system boundaries for establishing GHG emission inventories, particularly in the waste management sector, is a very special and difficult topic, it receives considerable attention in the present paper. This means that the system boundaries and interfaces with respect to three illustrative areas are considered in some depth. These areas are collection and transport, incineration and co-combustion, and biogas plants.

China is the world's largest energy consumer and CO2 emitter. Cities contribute 85% of the total CO2 emissions in China and thus are considered as the key areas for implementing policies designed for climate change adaption and CO2 emission mitigation. However, the emission inventory construction of Chinese cities has not been well researched, mainly owing to the lack of systematic statistics and poor data quality. Focusing on this research gap, we developed a set of methods for constructing CO2 emissions inventories for Chinese cities based on energy balance table. The newly constructed emission inventory is compiled in terms of the definition provided by the IPCC territorial emission accounting approach and covers 47 socioeconomic sectors, 17 fossil fuels and 9 primary industry products, which is corresponding with the national and provincial inventory. In the study, we applied the methods to compile CO2 emissions inventories for 24 common Chinese cities and examined uncertainties of the inventories. Understanding the emissions sources in Chinese cities is the basis for many climate policy and goal research in the future.

The environmental evaluation of fruits and vegetables in life cycle assessment (LCA) requires a proper estimation of pesticide emissions and associated (eco-)toxicity impacts. In response, we developed an approach to consistently combine state-of-the-art emission inventory and impact assessment models for assessing human toxicity and freshwater ecotoxicity impacts from pesticide applications, and tested our approach in an LCA case study on pesticides applied to an open-field tomato produced in Martinique (French West Indies). Our results show that impact scores vary over several orders of magnitude, mainly as function of differences in pesticide properties and application time in relation to crop growth stage. Overall, impacts related to pesticide field emissions leading to exposure to pesticide residues in crop harvest are a main contributor to LCA performance results for tomato produced in Martinique, with fertilizer and packaging manufacturing as other dominating aspects. While the proposed approach is applicable to refine currently LCA methods for assessing pesticides, large uncertainties remain. These are mostly related to the parametrization of impact factors for tropical species. Based on our findings, we recommend using initial emission distribution fractions in combination with steady-state characterization factors for environmental emissions and with time-dependent characterization factors for pesticide residues in crop harvest in LCA, while further improving the use of secondary emission fractions to allow for better consideration of local field, soil and climate characteristics.