Composting can divert organic waste from landfills, reduce landfill methane emissions, and recycle nutrients back to soils. However, the composting process is also a source of greenhouse gas and air pollutant emissions. Researchers, regulators, and policy decision-makers all rely on emissions estimates to develop local emissions inventories and weigh competing waste diversion options, yet reported emission factors are difficult to interpret and highly variable. This review explores the impacts of waste characteristics, pretreatment processes, and composting conditions on CO₂, CH₄, N₂O, NH₃, and VOC emissions by critically reviewing and analyzing 388 emission factors from 46 studies. The values reported to date suggest that CH₄ is the single largest contributor to 100-year global warming potential (GWP₁₀₀) for yard waste composting, comprising approximately 80% of the total GWP₁₀₀. For nitrogen-rich wastes including manure, mixed municipal organic waste, and wastewater treatment sludge, N₂O is the largest contributor to GWP₁₀₀, accounting for half to as much as 90% of the total GWP₁₀₀. If waste is anaerobically digested prior to composting, N₂O, NH₃, and VOC emissions tend to decrease relative to composting the untreated waste. Effective pile management and aeration are key to minimizing CH₄ emissions. However, forced aeration can increase NH₃ emissions in some cases.

Ambient particulate matter (PM) pollution is a major environmental health risk in urban areas. Dense networks of low-cost air quality sensors are emerging to characterize the spatially heterogeneous concentrations that are typical of urban settings, but are not adequately captured using traditional regulatory monitors at central sites. In this study, we present the 100×100 BC Network, a 100-day deployment of low-cost black carbon (BC) sensors across 100 locations in West Oakland, California. This 15 km² community is surrounded by freeways and affected by emissions associated with local port and industrial activities. We assess the reliability of the sensor hardware and data collection systems, and identify modes of failure to both quantify and qualify network performance. We illustrate how dynamic, local emission sources build upon background BC concentrations. BC concentrations varied sharply over short distances (∼100 m) and timespans (∼1 hour), depending on surrounding land use, traffic patterns, and downwind distance from pollution sources. Strong BC concentration fluctuations were periodically observed over the diurnal and weekly cycles, reflecting the impact of localized traffic emissions and industrial facilities in the neighborhood. Overall, the results demonstrate how distributed sensor networks can reveal the complex spatiotemporal dynamics of combustion-related air pollution within urban neighborhoods.

Emissions from thousands of in-use heavy-duty diesel trucks were sampled at a highway and an arterial street location in the San Francisco Bay Area, spanning a time period when use of diesel particle filters (DPFs) and selective catalytic reduction (SCR) increased rapidly. At the highway site where a diverse mix of trucks is observed, SCR systems on 2010 and newer engines reduce emitted nitrogen oxides (NO_x) by 87 ± 5% relative to pre-2004 engines. SCR also mitigates DPF-related increases in nitrogen dioxide (NO₂) emissions. However, a majority of trucks had in-use NO_x emission rates that exceeded applicable emission standards. SCR systems increase emissions of nitrous oxide (N₂O) and ammonia (NH₃) from near-zero levels to 0.93 ± 0.13 and 0.18 ± 0.07 g kg^–1, respectively. Emissions of all nitrogenous species and especially NH₃ are skewed; 10% of trucks contribute 95% of the on-road fleet’s total NH₃ emissions. Similar emission changes are observed at the arterial street site where exclusively drayage trucks operate. The environmental effects of decreased black carbon, NO_x, and carbon dioxide (CO₂) emissions and increased N₂O and NH₃ emissions due to the rapid adoption of DPF and SCR systems by the California truck fleet are: (1) a 65% net decrease in the social cost of statewide exposure to diesel truck emissions (−3.3 billion 2018 US dollars per year), and (2) a 3% net decrease in the global warming potential-weighted emission factor (−27 g CO₂-eq km^–1).